Meeting Title: Brainforge Recruitment Call with Shreya Date: 2025-08-13 Meeting participants: Uttam Kumaran, Shreya Chowdhury
WEBVTT
1 00:07:24.220 ⇒ 00:07:25.150 Shreya Chowdhury: Hello?
2 00:07:31.420 ⇒ 00:07:32.809 Uttam Kumaran: Hey, how’s it going?
3 00:07:33.330 ⇒ 00:07:34.430 Shreya Chowdhury: How are you?
4 00:07:34.430 ⇒ 00:07:37.850 Uttam Kumaran: Good. Thanks for taking the time. How’s it going this week?
5 00:07:38.070 ⇒ 00:07:42.890 Shreya Chowdhury: Sorry I joined late, I don’t know what it was, but I wasn’t able to connect my microphone for a while.
6 00:07:42.890 ⇒ 00:07:44.549 Uttam Kumaran: No, you’re okay, no worries.
7 00:07:45.580 ⇒ 00:08:03.810 Uttam Kumaran: Yeah, I got your, I got your contact from Jamie. You know, I usually text a group of friends when we’re starting to, you know, grow the team, and he mentioned that maybe he’d be someone interesting to, to reach out to and just say hi to. So, yeah, that’s kind of how we got put in contact.
8 00:08:04.180 ⇒ 00:08:09.329 Shreya Chowdhury: Yeah, that’s great. I’m really glad that he did that, and I was super happy to hear from you.
9 00:08:09.330 ⇒ 00:08:14.889 Uttam Kumaran: Yeah, how do you, … how did you end up meeting Jamie? Do you guys work on stuff together, or, ….
10 00:08:14.890 ⇒ 00:08:28.739 Shreya Chowdhury: Yeah, so we worked on Shopify together. We were in the same overarching org. We weren’t on the same, like, direct team, but we were in the same org, so we would,
11 00:08:28.740 ⇒ 00:08:37.819 Shreya Chowdhury: We had, like, a rough gauge of, like, what the other person was working on and what we were doing, and occasionally we would have, like, one-on-ones and pair on stuff together.
12 00:08:37.820 ⇒ 00:08:48.570 Uttam Kumaran: Nice. Okay, cool. Yeah, I worked with Jamie in my first job at WeWork. I was… I live in Austin now, but I used to live in the city, and yeah, we were…
13 00:08:48.920 ⇒ 00:08:49.640 Uttam Kumaran: …
14 00:08:49.810 ⇒ 00:08:58.409 Uttam Kumaran: we were just, like, both just out of school working on, like, on a bunch of projects there, so it was really great, and yeah, we kept in touch. …
15 00:08:58.540 ⇒ 00:09:09.120 Uttam Kumaran: But yeah, I don’t know how much, you know, if you mentioned anything at all about the company. I know I sent a little bit of a brief blur, but I’m happy to, you know, share a little bit about us, and then, yeah, just curious to hear, like.
16 00:09:09.120 ⇒ 00:09:20.119 Uttam Kumaran: What you’re up to, if, like, a role or an opportunity would be interesting, but also curious, like, what part of the data stack you’ve worked in, and, like, kind of what your goals are as well.
17 00:09:20.540 ⇒ 00:09:21.920 Shreya Chowdhury: Yeah, …
18 00:09:22.050 ⇒ 00:09:38.919 Shreya Chowdhury: So, I can… I can tell you a little bit about myself. I did take a peek at your website, and I was, like, looking through that a little bit before our meeting. Yeah, and I… I think it’s really interesting work, like, what you’re doing. I can tell you a little bit about my…
19 00:09:38.920 ⇒ 00:09:46.239 Shreya Chowdhury: skill set, and where and how… I don’t… you can tell me where and how that might fit into what you’re looking for.
20 00:09:46.240 ⇒ 00:09:46.590 Uttam Kumaran: Under….
21 00:09:46.940 ⇒ 00:09:52.420 Shreya Chowdhury: Basically, I was, like, full stack at Shopify, so it was kind of like…
22 00:09:53.060 ⇒ 00:10:01.860 Shreya Chowdhury: data analyst, data engineer, like, everything in between. So it would be, like, …
23 00:10:02.520 ⇒ 00:10:07.690 Shreya Chowdhury: Like, yeah, like, building a lot of the data pipelines, like, …
24 00:10:07.790 ⇒ 00:10:22.949 Shreya Chowdhury: Like, ones that we knew we needed, and then also sometimes, like, assessing, like, the data needs and the data quality, and figuring out, like, how we want to model the data, and, building those data models, and then eventually,
25 00:10:23.490 ⇒ 00:10:28.849 Shreya Chowdhury: Building, like, reports and dashboards, like, using those data models, and then also, like.
26 00:10:28.890 ⇒ 00:10:48.840 Shreya Chowdhury: doing, analyses using those data models, and then, like, doing, like, technical write-ups on those analytics. I have some experience with A-B testing, like, experimentation, and some causal inference models,
27 00:10:49.270 ⇒ 00:10:58.220 Shreya Chowdhury: I’ll take a brief pause there, because that covers, like, the bulk of it. Like, it was a lot of product analytics and…
28 00:10:58.360 ⇒ 00:11:02.709 Shreya Chowdhury: Data modeling mostly, with, like, some other stuff in between.
29 00:11:02.710 ⇒ 00:11:09.690 Uttam Kumaran: Was there a specific, like, domain, or was it sort of across the board? Like, were you guys supporting one or many teams?
30 00:11:09.970 ⇒ 00:11:21.749 Shreya Chowdhury: Yeah, so I was on two teams, so I… we had, like, two major marketplaces, which were, like, our app store and our theme store for merchants.
31 00:11:21.750 ⇒ 00:11:41.659 Shreya Chowdhury: Theme Store was a lot smaller, and it was in maintenance mode for many, many years, but I pretty much owned that entire space on my own for, like, 3 years. And then on the App Store, App Store was much bigger, so that was, like, spread across our entire team. I owned the…
32 00:11:41.660 ⇒ 00:11:55.250 Shreya Chowdhury: like, taxonomy of the App Store, so every app store basically had, like, a subcategory, a category, and other, like, things that it belonged to, so I owned all the data models related to that. Okay.
33 00:11:55.250 ⇒ 00:11:55.760 Uttam Kumaran: Cool.
34 00:11:56.110 ⇒ 00:11:56.580 Shreya Chowdhury: Yeah.
35 00:11:56.580 ⇒ 00:12:04.700 Uttam Kumaran: was… what was the, like, overall stack? Was it, … yeah, if you can go into, like, what the warehouse was, if you guys were using dbt, like, what the…
36 00:12:04.780 ⇒ 00:12:17.089 Uttam Kumaran: And then, kind of more curious also about, like, when it comes to visualization and reporting, like, what… how were the ways that you actually got data to… to stakeholders, and were stakeholders, like, analysts, or were they business people? Yeah, if you could just talk about, like.
37 00:12:17.180 ⇒ 00:12:20.939 Uttam Kumaran: Maybe more technical, like, on each part of the stack.
38 00:12:21.510 ⇒ 00:12:24.340 Shreya Chowdhury: Yeah, sounds great. So…
39 00:12:24.410 ⇒ 00:12:35.679 Shreya Chowdhury: our stack, we… we did use dbt, a lot more initially, and we used to have most of our data models in Starscream.
40 00:12:35.680 ⇒ 00:12:46.420 Shreya Chowdhury: Eventually, like, in the last couple years, we switched to, like, Shopify built its own, data warehouse. …
41 00:12:46.870 ⇒ 00:12:58.789 Shreya Chowdhury: So we would have, like, we built… we had all of our data models, like, migrated, to our new, Shopify’s new data platform, and then…
42 00:12:58.790 ⇒ 00:13:07.269 Shreya Chowdhury: We also built the new ones in that data warehouse. For that one, yeah, we mostly use dbt, …
43 00:13:07.670 ⇒ 00:13:18.530 Shreya Chowdhury: for analyses and, like, reporting and getting the data to stakeholders, we used to use this thing called mode reports, … Okay.
44 00:13:18.530 ⇒ 00:13:28.800 Shreya Chowdhury: I was a fan of that. I thought it was, like, very simple and easy to use, and it did a good job of integrating, like, visualizations from both Python notebooks
45 00:13:28.800 ⇒ 00:13:33.129 Shreya Chowdhury: and, like, the sequel that you would draw. Eventually, we…
46 00:13:33.340 ⇒ 00:13:38.250 Shreya Chowdhury: stopped using Mode, and we switched to Looker. Okay.
47 00:13:39.180 ⇒ 00:13:58.140 Shreya Chowdhury: Looker is okay. I think it has a lot of capacity in terms of, like, building reports and, like, visualizations and stuff. I… my preference is still Jupyter Notebooks, probably, or Mode, but I’m… I’m familiar with all three. Okay.
48 00:13:58.570 ⇒ 00:14:10.440 Shreya Chowdhury: So, yeah, that’s kind of what we used for that. And as far as, like, where we would do querying, it was in the Google Cloud, console, and we used… Yeah.
49 00:14:10.980 ⇒ 00:14:23.779 Uttam Kumaran: Okay, okay. So yeah, I mean, in our world, so maybe a little bit about my background. So I worked, you know, I worked at WeWork with Jamie, and then went to this company called, Flowcode. It was a QR code startup in New York.
50 00:14:23.980 ⇒ 00:14:36.189 Uttam Kumaran: I… yeah, I joined right before COVID, and then it kind of exploded as everyone started using QR codes, but now you’ll kind of see… you’ll see them, like, if you watch, sports, or if you’re at…
51 00:14:36.190 ⇒ 00:14:48.979 Uttam Kumaran: restaurants, or it’s on a lot of TV stuff now, like, I was watching, Love Island US, and with my girlfriend, and at the end, the sidecard has a flow code on it to, like, scan
52 00:14:49.140 ⇒ 00:14:59.980 Uttam Kumaran: to vote on whoever. So, like, that company blew up, so I was, like, leading data there, and then built out also their customer-facing, like, analytics product.
53 00:15:00.060 ⇒ 00:15:18.459 Uttam Kumaran: And then I went to a company called Prequel, where I was, leading product there. And then, yeah, I moved to Austin, like, 3 years ago, and then 2 years ago, I just quit that job, and sort of deciding what to do. And, you know, I’d done some contracting and consulting before, and was sort of, you know, curious about if I could
54 00:15:18.510 ⇒ 00:15:22.209 Uttam Kumaran: Do something there, but not really as a way of, like, picking up
55 00:15:22.370 ⇒ 00:15:31.839 Uttam Kumaran: like, trying to just, like, hold two contracts and, like, make double money, like, actually try to start a consultancy. I just think a lot of consultants and data, like, tend to suck.
56 00:15:31.950 ⇒ 00:15:49.539 Uttam Kumaran: And I don’t think they’re… they’re often, like, better than the people in the company, and I think when you bring in a consultant, you’re bringing them in for one or more reasons. Like, one is, like, you’re in a tight jam, like, you need someone now. Someone that can hop into any environment.
57 00:15:49.880 ⇒ 00:15:56.860 Uttam Kumaran: figure out, like, what the problem is, and then start to solve problems. You’re also bringing in people because it’s really difficult to hire.
58 00:15:56.860 ⇒ 00:16:13.140 Uttam Kumaran: like, it’s not very easy to get great data people these days. Often, you know, you can’t… especially in an environment like consulting, where we work with so many different types of clients, you need people whose, like, general mindset is kind of like, whatever situation I’m in, I’ll…
59 00:16:13.170 ⇒ 00:16:23.890 Uttam Kumaran: I’ll boss up, you know, kind of thing. So, I think we’ve done a good job in that we’re completely bootstrapped. I started the company 2 years ago, and we’re about 15 people now.
60 00:16:24.210 ⇒ 00:16:27.280 Uttam Kumaran: And we’ve worked with almost, like, 40 different clients
61 00:16:27.350 ⇒ 00:16:36.259 Uttam Kumaran: You know, since then. All in, like, you know, some engagements are, kind of narrow, some engagements are… we’ve now been working with companies over a year and a half.
62 00:16:36.270 ⇒ 00:16:55.729 Uttam Kumaran: So it’s… it’s been kind of an interesting ride. I think where we’re at now is we’re just trying to get… continue to get great data people, but also people that have sort of seen, how it works at larger companies. You know, the company started, we were working for startups and, like, kind of whoever we can get. Now, we were working for mainly mid-market
63 00:16:55.740 ⇒ 00:17:12.579 Uttam Kumaran: private businesses, and consistently growing. So, these are, like, businesses that are 20 to 100 million in revenue. We don’t work with many startups anymore, unless, like, I have a personal connection. Even then, trying to say no to them, just because they tend to…
64 00:17:12.630 ⇒ 00:17:14.940 Uttam Kumaran: To suck as clients. …
65 00:17:15.040 ⇒ 00:17:32.660 Uttam Kumaran: So, yeah, that’s kind of, like, where we are. I mean, we work with so many different stacks, like, we have clients on Looker, Tableau, we use some more modern BI tools that are, like, more BI as code. We also, like, use dbt pretty much across the board, but on the warehouse side.
66 00:17:32.780 ⇒ 00:17:46.879 Uttam Kumaran: it can totally depend, also, if we’re walking into an environment, or if we’re able to make the decision on what to bring. So it is really, like, kind of like full-stack data, but we do have roles, like, we do have people that are just on the analyst side.
67 00:17:46.880 ⇒ 00:17:55.530 Uttam Kumaran: on the AE side, and then on the DE side, but, you know, for me, my background, I’m also kind of like you, I’m sort of full-stack data, so…
68 00:17:55.550 ⇒ 00:18:05.300 Uttam Kumaran: I don’t really care where I get tossed in, and we have, like, one or two people like that where, they can kind of get put wherever. But, you know, you kind of have your…
69 00:18:05.300 ⇒ 00:18:18.779 Uttam Kumaran: your favorite. Like, for me, I like to do a lot of modeling work, and I like to do a lot of DE work. I can… I’ve done a lot of analyst work, but it’s not my favorite, and it can be very subjective, and it takes a lot of work to meet with clients and do that, but…
70 00:18:18.860 ⇒ 00:18:27.320 Uttam Kumaran: So that’s kind of, like, where we are, and kind of the reason why I’m, like, we’re looking for more people is we’re growing, so we’re… we’re bringing on a lot of really interesting clients.
71 00:18:27.320 ⇒ 00:18:41.289 Uttam Kumaran: all of them are struggling with data in one way or another. And then I, you know, really, I didn’t even talk much about, sort of, a lot of the AI work that we’re doing, but we’re also doing, you know, half of our business is in AI.
72 00:18:41.320 ⇒ 00:18:45.070 Uttam Kumaran: We… I used AI really significantly to build a business.
73 00:18:45.120 ⇒ 00:19:01.750 Uttam Kumaran: Over the last 2 years, and in that process over the last year, we decided that we had built a lot of systems for ourselves, and we learned about how to build agents, kind of before a lot of things became really mainstream. And certainly before, even now, where people don’t know how to do a lot of the
74 00:19:01.890 ⇒ 00:19:12.710 Uttam Kumaran: like, how to build agents and actually get adoption in AI in their businesses. So, yeah, we have several clients where we’re actually implementing AI agents and building agentic workflows and RAG systems for
75 00:19:12.740 ⇒ 00:19:23.369 Uttam Kumaran: And then, kind of finally, is we’re trying to find ways to merge the two. So, how can we, as part of our data offering, deploy agents to help, you know, people make decisions?
76 00:19:23.380 ⇒ 00:19:33.830 Uttam Kumaran: And then also, like, all of our engineers on our… in our company use Cursor for everything, like, we’re… we’re trying to just become very AI-native, so all of our project managers use AI.
77 00:19:33.830 ⇒ 00:19:51.479 Uttam Kumaran: For meeting notes, for, you know, creating tickets, like, everywhere we are, we have, like, a little internal AI platform team. So, that’s sort of, like, the state of the company right now, and where we are. Kind of open to answering, you know, any questions or any thoughts you have on that.
78 00:19:52.170 ⇒ 00:20:05.949 Shreya Chowdhury: Yeah, I think you covered, like, some of my questions. I was going to ask about, like, how you guys have been adopting AI, and core clients right now. I think you said you’re mostly focused on mid-market,
79 00:20:05.950 ⇒ 00:20:13.780 Shreya Chowdhury: and not startups as much. Yeah, AI too, at Shopify, like, we were very, very bullish on AI, and there were, like.
80 00:20:13.840 ⇒ 00:20:25.179 Shreya Chowdhury: tools, there are plenty of tools across the board. I used Cursor a lot, like, especially in the last, like, I want to say, like, 3 to 4 months, like, we used Cursor a lot,
81 00:20:26.040 ⇒ 00:20:27.950 Shreya Chowdhury: Before that, it was like…
82 00:20:28.110 ⇒ 00:20:40.829 Shreya Chowdhury: I would use it a lot in when I would be drafting, like, a doc for analytics, but yeah, I tend to use it, like, incorporate it a lot. It’s very easy for me to have, like.
83 00:20:41.140 ⇒ 00:20:58.459 Shreya Chowdhury: someone to, like, code pair with, and, like, someone to talk through a lot of the analyses and stuff. So I really like that. I think that’s great. I think you also answered this, but one of my questions was, like, if you had a preference for specialized roles, or if you’re leaning towards people who can, like.
84 00:20:58.600 ⇒ 00:21:09.019 Shreya Chowdhury: I don’t know, wear a lot of hats. I’m also fine with either, like, being put in a specific role if, like, that’s what you’re looking for, but I do tend to like…
85 00:21:09.020 ⇒ 00:21:21.819 Shreya Chowdhury: kind of the full-stack work, too, because it keeps things a little dynamic. So, like, if I work on, like, DE for a while, and afterwards I’m like, oh, like, it would be nice to do some analytics, like, as a, like, palette cleanser and come back,
86 00:21:21.820 ⇒ 00:21:27.100 Shreya Chowdhury: I like that, like, working… like, workflow, but I’m….
87 00:21:27.100 ⇒ 00:21:33.800 Uttam Kumaran: Much more of the latter. Like, my background is in sort of shape-shifting.
88 00:21:33.800 ⇒ 00:21:51.379 Uttam Kumaran: just for whatever the problem is, and look, in our engagements, we come in as data people, but we sell to the C-suite and, like, to the operators in the company. So often, they’re not very opinionated on how we do it, they want the outcomes, right? Like, they want reports to be available for their team.
89 00:21:51.380 ⇒ 00:21:56.450 Uttam Kumaran: They want to be able to create their board decks, like, that’s the outcome that matters, and so…
90 00:21:56.450 ⇒ 00:22:12.119 Uttam Kumaran: It’s a little bit different than working in a company in that it’s, one, it’s a lot more communication, and, like, you’re always kind of under the gun a little bit, because as consultants, someone is, every month or every quarter is like, who are these guys? Are they worth it?
91 00:22:12.120 ⇒ 00:22:30.080 Uttam Kumaran: But in a similar lens, we come in and we’re like Navy SEALs, right? We come in and we go direct to the prom, we don’t have to deal with any politics, we don’t have to go to any of their meetings, like, we run stand-ups ourselves. We often absorb their existing data team, or their whatever, their one or two data people.
92 00:22:30.080 ⇒ 00:22:34.999 Uttam Kumaran: And we become the most organized team in their business, just because, you know, we’ve…
93 00:22:35.000 ⇒ 00:22:45.429 Uttam Kumaran: I’ve ran data teams before, and I can sort of direct, you know, how we’re gonna actually execute. And so, it’s… it’s nice in that you can play multiple hats, although we typically…
94 00:22:45.520 ⇒ 00:22:54.990 Uttam Kumaran: we… you tend to, like, have a little bit of swim lanes where people like to exist, right? Like, someone like me, and we have some people in the company, that can go anywhere, but
95 00:22:54.990 ⇒ 00:23:09.640 Uttam Kumaran: a lot of our strength is in data modeling, data engineering. We have some people that are more analyst-heavy, and yeah, they can stretch to do data modeling, but at some point, it’s also kind of a question about, like, how the project manager on your team wants to sort of handle things. But I prefer
96 00:23:09.640 ⇒ 00:23:19.959 Uttam Kumaran: people that can do multiple things, because you also create redundancy, right? Like, if people are out, and you create lanes for reviews, so multiple people can take on
97 00:23:19.970 ⇒ 00:23:28.069 Uttam Kumaran: any task, and… and then you can kind of decide, like, on one project, you can be just focused on modeling, on another project could be more analysis, and
98 00:23:28.320 ⇒ 00:23:29.510 Uttam Kumaran: Like, I don’t…
99 00:23:29.660 ⇒ 00:23:40.559 Uttam Kumaran: I don’t particularly care either way. I’m not sure what the right answer is from, like, a consulting person, but I’m… I’m… as a person who leads, you know, we’re… if you think about it, we’re leading, maybe.
100 00:23:40.710 ⇒ 00:23:55.569 Uttam Kumaran: 10 or so data teams in parallel right now, like, I care more about the outcome. And whatever team structure allows us to do that is best. And additionally, I think a lot of people who are in industry, they often
101 00:23:55.750 ⇒ 00:24:04.259 Uttam Kumaran: They have people wearing multiple hats, but then what you get is you get a team of, like, 100 people, and everybody just kind of throws bombs over the fence to each other.
102 00:24:04.400 ⇒ 00:24:20.539 Uttam Kumaran: And I think we can get a lot of work done just with, like, a couple people. I mean, I know that for a fact, and so… I don’t care… I don’t care much about, like, headcount, I care more about, like, outcomes for… for the team, and for my business, I would much rather have less people making more money.
103 00:24:20.590 ⇒ 00:24:25.869 Uttam Kumaran: like, that’s a much better system with a lot less bloat, you know, especially in a consultancy where.
104 00:24:26.340 ⇒ 00:24:39.530 Uttam Kumaran: typically, like, the natural tendency is to hire really fast, and so one thing that we’ve tried to do is sort of keep that at bay as much as possible, both using AI, but also just, like.
105 00:24:39.680 ⇒ 00:24:44.219 Uttam Kumaran: Kind of, like, innovating on how to run a consultancy that’s… that’s not, like.
106 00:24:44.440 ⇒ 00:25:00.599 Uttam Kumaran: by the book, in that we… we do things more like an internal engineering team would, where we… we map people to, sort of, goals and outcomes, versus, like, okay, you get 10 people here, 10 people there, like, it doesn’t… it doesn’t solve anything, typically. So I think that’s one of the unique things about
107 00:25:00.710 ⇒ 00:25:14.130 Uttam Kumaran: this company is it’s not a… most, like, kind of IT consultancies, there’s no, like, camaraderie between teams, there’s no, like, shared, like, learnings, there’s almost, like, very limited sense of, like, a platform. …
108 00:25:14.540 ⇒ 00:25:26.839 Uttam Kumaran: In consulting, because typically you come into a client, and you’re kind of isolated to a client. Like, if you talk to anyone into consulting after this, they’ll kind of share with you that you often don’t meet people who are on other clients, or maybe there’s, like, a…
109 00:25:27.510 ⇒ 00:25:39.649 Uttam Kumaran: entire company thing, like, once a quarter, but there’s never, like, shared learnings. And for us, that’s, like, kind of, like, what our alpha is, because every additional client gains from the stuff we learned from the previous one.
110 00:25:39.650 ⇒ 00:25:49.939 Uttam Kumaran: And, yeah, we need to sort of operate as, like, almost like a data team that is supporting several different clients, right? It’s not as… it’s not that dissimilar to, like, a decentralized
111 00:25:50.020 ⇒ 00:26:09.160 Uttam Kumaran: data team in a company, it’s kind of just that on, like, hard mode, where not all… it’s just those different folks we’re supporting are not all in the same company, but there are a lot of shared learnings that we try to make sure everyone has access to. And then, yeah, for me, it’s like, that’s… that’s what I like. Like, I don’t want to build
112 00:26:09.510 ⇒ 00:26:26.249 Uttam Kumaran: a company where the engineer… like, this is a really engineering-heavy company. Both me and my business partner are engineers, most of the people in the company are engineers, so it’s more focused on that versus, like, okay, there’s one client you’re assigned to, and you don’t get to talk to anybody else. It’s… it’s a lot… it’s a lot less of that.
113 00:26:27.930 ⇒ 00:26:44.990 Shreya Chowdhury: Okay, yeah, I mean, that all sounds really great. I think you asked me a question earlier that I, I may have forgotten to verify, but I think you also asked, who my main stakeholders was when I was working at Shopify. As you were talking about it,
114 00:26:45.290 ⇒ 00:26:58.899 Shreya Chowdhury: it reminded me, so I… we had, what was called embedded teams, so I had technical stakeholders, and that would be, like, our data org and our data team, so a lot of the engineering work I would do,
115 00:26:59.250 ⇒ 00:27:07.830 Shreya Chowdhury: my stakeholders would be our data team, and it would be like, oh, I know this person will be using, like, these data models, or I’m helping build, … Right.
116 00:27:07.830 ⇒ 00:27:26.349 Shreya Chowdhury: like, data models in a specific area that someone else is gonna use, and then we had our cross-functional team, which would usually be, like, a team of, like, a few developers, a few, like, UX designers, one project manager, and then one data scientist. And so there, my stakeholders would pretty much be, like.
117 00:27:26.350 ⇒ 00:27:31.280 Shreya Chowdhury: everyone on the team, and whatever data they would leverage, and that one was very, like.
118 00:27:31.320 ⇒ 00:27:34.580 Shreya Chowdhury: shapeshift-y, like, you are whatever you need to be.
119 00:27:34.580 ⇒ 00:27:35.100 Uttam Kumaran: Yeah.
120 00:27:35.100 ⇒ 00:27:38.499 Shreya Chowdhury: UI, like, is designing, like, the new, like.
121 00:27:38.870 ⇒ 00:27:52.869 Shreya Chowdhury: I don’t know, they have multiple headers or multiple, like, whatever it is, like, I would be in charge of, like, running the A-B test to see, like, the results and figure out, like, which one we use. If it was, like, building a new search rankings model for, like.
122 00:27:52.980 ⇒ 00:28:01.550 Shreya Chowdhury: app display or theme display, like, I would be working on pulling the data to figure out, like, what numbers we use in the algorithm,
123 00:28:01.550 ⇒ 00:28:02.100 Uttam Kumaran: Yeah.
124 00:28:02.100 ⇒ 00:28:15.049 Shreya Chowdhury: And then, like, kind of assess, like, pre, like, preliminary, like, impacts that a feature might have, and then also impact, like, assess impact of features launched afterwards, …
125 00:28:15.420 ⇒ 00:28:29.889 Shreya Chowdhury: So yeah, that’s kind of, like… I have experience on both ends, too. Like, I’ve had both technical and non-technical stakeholders. So I think that was, like, a good experience, because you learn how to communicate, like, with different people.
126 00:28:29.890 ⇒ 00:28:30.900 Uttam Kumaran: However, yeah.
127 00:28:30.900 ⇒ 00:28:34.669 Shreya Chowdhury: So it’s like, obviously when you’re dealing with, like.
128 00:28:35.150 ⇒ 00:28:43.220 Shreya Chowdhury: an audience that is a little more tech-savvy, it’s like, you want to get more into the nitty-gritty of, like, what you’re doing. But I think it’s also, like.
129 00:28:43.600 ⇒ 00:28:48.060 Uttam Kumaran: there’s a little bit of fun to, like, data storytelling. Yes.
130 00:28:48.060 ⇒ 00:28:49.970 Shreya Chowdhury: non-Data folk, and that.
131 00:28:49.970 ⇒ 00:29:07.100 Uttam Kumaran: Well, that’s, like, what’s a lot of our work is now, is that actually, you know, a lot of our work isn’t that technically challenging. Like, I don’t think anything that you’ll see at our company… at our company is, like, anything harder than I even did at, like, WeWork. Like, it’s… it’s actually the fact that we’re going to companies that have so little support.
132 00:29:07.210 ⇒ 00:29:21.629 Uttam Kumaran: Yeah. Or they’ve been, like, left in the dust by, like, someone who came in, built a lot of stuff, and then left. Or they’re, like, they just recently, like, adopted cloud stuff. Like, it’s so painful, some of the companies we go in, and these are… a lot of them are, like, household names, like…
133 00:29:21.630 ⇒ 00:29:27.400 Uttam Kumaran: Like, pretty big companies that you’re, like, so surprised that they’re not running their stuff in a data-driven manner.
134 00:29:27.410 ⇒ 00:29:42.219 Uttam Kumaran: Which, for me, is actually, like, what I love, because at, like, at a lot of the companies I worked at, like, we were solving problems that, yeah, maybe you get from, like, 95 to 96th percentile, but these are companies where, like, they don’t even have, like, DBT,
135 00:29:42.220 ⇒ 00:29:50.200 Uttam Kumaran: they’re running queries on their Postgres, like, direct, and, like, someone has, like, queries saved on their desktop, like, and they’re making $50 million a year.
136 00:29:50.240 ⇒ 00:29:50.790 Uttam Kumaran: Yeah.
137 00:29:50.790 ⇒ 00:29:51.510 Shreya Chowdhury: That’s….
138 00:29:51.740 ⇒ 00:30:02.529 Uttam Kumaran: It’s insane, like, you’ll never expect the kind of the stuff we’re seeing, but in that sense, there’s also a reason they’re there, right? Someone didn’t believe in investing in data, or maybe they invested in it and it got burned.
139 00:30:02.640 ⇒ 00:30:12.769 Uttam Kumaran: Right? Or they’ve had a lot of data people, but no one’s ever, like, sort of brought everyone together and led an initiative and, like, set goals, set KPIs, like…
140 00:30:13.050 ⇒ 00:30:24.329 Uttam Kumaran: bake the whole pie, right? So there’s all these reasons, and for us, like, we have to figure out the reasons, and the people involved, and the incentives of those people, right? Like, why do they care that this gets done?
141 00:30:24.330 ⇒ 00:30:34.170 Uttam Kumaran: And our job is that the fact that, like, Brainforge isn’t the company that needs to get famous, it’s the people we support, right? So my job is, whoever we support, they need to be, like, made the hero.
142 00:30:34.440 ⇒ 00:30:43.429 Uttam Kumaran: And so my… that’s our goal, is like, okay, find the stakeholder, how do we champion that person? We will… we’ll win if they win. That’s all we care about.
143 00:30:43.580 ⇒ 00:31:03.219 Uttam Kumaran: I think a lot of other consultancies come in and, like, they come in with, like, 100 decks, they, like, okay, well, we need 10 people to do this, and everybody’s, like, offshore, and there’s no, like, personality, like, it’s really horrible. And I think we’ve won because we’ve sort of done things a little bit of a different way. Granted, there’s, like.
144 00:31:03.220 ⇒ 00:31:17.270 Uttam Kumaran: there’s a cost to doing that, and we’ve messed up a lot, but, I think what we’ve seen is that since we’ve been able to work with so many different companies, and you’re right, it’s a lot of storytelling, and it’s a lot of communication, and there’s still a lot of
145 00:31:17.380 ⇒ 00:31:31.610 Uttam Kumaran: great technical work to be done, but most of it is, like, translating to the next company why dbt matters, like, why, … why you should actually push your BI logic into code versus having it in Looker, things like that, right? So, and we’re…
146 00:31:31.630 ⇒ 00:31:43.810 Uttam Kumaran: And then, internally, we build playbooks for all of this, so the next company we go to, we can do this even faster. We can… because we do faster, we can charge more, you know, and it’s kind of a great cycle in that… in that sense.
147 00:31:45.830 ⇒ 00:31:50.909 Shreya Chowdhury: Yeah, that sounds… That sounds great, I really like…
148 00:31:50.940 ⇒ 00:32:15.660 Shreya Chowdhury: like, a lot of what you said, and I think it’s, like, that part is always interesting to me, because it’s, like, when you come in from an initial state, and you see, like, what the data needs are, like, one, you have a lot more creative autonomy in, like, the data foundation, and I think that’s one of the most important work, too, is, like, building the data foundation for a company, especially, like, the mid-market companies, like, they’re big companies, and they have
149 00:32:15.660 ⇒ 00:32:20.199 Shreya Chowdhury: Like, they can be really successful by leveraging data. …
150 00:32:21.160 ⇒ 00:32:32.160 Shreya Chowdhury: coming from a background where, like, like, in our ecosystem, like, for theme stores specifically, like, there would be times where you really have to cut a lot of corners, or, like.
151 00:32:32.550 ⇒ 00:32:35.650 Shreya Chowdhury: work with, like, low-quality data. It was, like.
152 00:32:35.650 ⇒ 00:32:36.230 Uttam Kumaran: Yeah.
153 00:32:36.230 ⇒ 00:32:53.360 Shreya Chowdhury: really refreshing, like, in the last few months, when my main projects were basically like, oh, like, now that we’re reinvesting in Themeestore and you know the space, like, help us build a good data foundation, because all of this data sucks. So I think, like, that’s really, like, cool work. ….
154 00:32:53.730 ⇒ 00:33:06.679 Uttam Kumaran: Yeah, I guess my next question is sort of, like, now that you’ve seen all of that, what’s your… what’s your goal? Like, what do you think about in your career? Like, what your goal is and where you want to fit? I mean, a consulting company is a lot different.
155 00:33:06.850 ⇒ 00:33:08.320 Uttam Kumaran: Pass, then…
156 00:33:08.440 ⇒ 00:33:15.079 Uttam Kumaran: you know, going back into a single company, but there are a lot of benefits. I guess I’m curious, like, where you see yourself, and…
157 00:33:15.240 ⇒ 00:33:21.649 Uttam Kumaran: You know, whether you want to go into management, whether you want to kind of still do more heavy data work, like, where… what you’re thinking about.
158 00:33:21.820 ⇒ 00:33:37.910 Shreya Chowdhury: Yeah, so, honestly, I was super pleasantly surprised, to get your text, because I haven’t been, like, recruiting super heavily, like, I’ve applied to, like, some companies here and there, but they’re all, like, big tech, very, like, specific roles, like, going into, like… Yeah.
159 00:33:38.270 ⇒ 00:33:39.100 Shreya Chowdhury: like…
160 00:33:39.430 ⇒ 00:33:49.589 Shreya Chowdhury: I don’t think the roles are, like, exactly similar to what I was doing before, but, like, similar-esque. But when I saw, like, what you were doing, like, I think it’s, like.
161 00:33:49.590 ⇒ 00:33:59.590 Shreya Chowdhury: it’s very interesting, and it’s, like, what I would ideally, like, the type of space that I would like to be working on, where it’s, like, you still can kind of stay, like, full stack, like, you’re, like.
162 00:33:59.590 ⇒ 00:34:08.299 Shreya Chowdhury: I don’t know, wearing a bunch of different hats, doing whatever, and it’s… it’s less… it’s just, like, a lot more dynamic and interesting work, so I think as far as that, like.
163 00:34:08.630 ⇒ 00:34:12.209 Shreya Chowdhury: The projects that you’re working on and what you’re doing is, like.
164 00:34:12.520 ⇒ 00:34:28.689 Shreya Chowdhury: exactly what I’d want to be doing. Like, I like consultancy because it’s, like, one, not just dynamic in the exact technical role I would take, but also in terms of, like, you get to work with a lot of different clients, like, you get to see how data would fit into a lot of different spaces, and that’s…
165 00:34:28.690 ⇒ 00:34:38.839 Shreya Chowdhury: like, a type of job that I’ve always wanted to have, but I’ve never had before. It’s always been, like, at a company, and it’s like, oh, like, this is the project you’re assigned, and you.
166 00:34:38.840 ⇒ 00:34:40.620 Uttam Kumaran: Same. Me too.
167 00:34:40.620 ⇒ 00:34:43.380 Shreya Chowdhury: It’s not bad, like, it’s great.
168 00:34:43.389 ⇒ 00:34:59.549 Uttam Kumaran: It’s not bad, but you have to go really deep, and I just… I don’t know, we’re getting a lot of, like… we’re going into companies that are so far behind. It’s kind of the companies you hear about, where you’re like, wow, like, they have nothing, and they have all this money, but it’s funny because they’re not a tech company.
169 00:34:59.619 ⇒ 00:35:11.050 Uttam Kumaran: So they’re not, like, they’re not focused on, like, data is not their number one, they’re not, like, going to data talks, like, it’s so different than a lot of the big tech that I’m used to. I saw one….
170 00:35:11.050 ⇒ 00:35:20.879 Shreya Chowdhury: the, I think it was, like, the coconut water brand, like… Yeah. Yeah, like, I… I thought that was so funny, I was like, dang, like, I have, like, 3 on my desk right now.
171 00:35:20.880 ⇒ 00:35:38.790 Uttam Kumaran: Yeah, so these are brands you wouldn’t know of, and my friend is, like, a senior person on the IT department called me one day, and yeah, they’re running on, like, you can’t… you have to log into, like, a virtual… like, a virtual server. They’re… they’re using Power BI and SQL Server. It’s horrible. It’s, like, the worst thing ever.
172 00:35:38.790 ⇒ 00:35:42.880 Uttam Kumaran: And yet, they’re in every bodega in New York, like, everybody knows Vladoco.
173 00:35:42.880 ⇒ 00:35:47.650 Uttam Kumaran: You know, very similarly, we started working with Insomnia Cookies recently.
174 00:35:48.010 ⇒ 00:36:04.939 Shreya Chowdhury: Yeah, I think you mentioned that one, too. I was like, that, like, that to me was, like, I think you have really interesting clients, and that’s, like, really fun, because it’s, like, you get to dip your toe in a little bit of, like, so many fields that you wouldn’t expect to, but it’s like, oh my god, like, you’re working with data, like, setting up data for, like.
175 00:36:04.940 ⇒ 00:36:07.530 Uttam Kumaran: Or, like, these brands, yeah, and they have a great….
176 00:36:07.530 ⇒ 00:36:08.150 Shreya Chowdhury: Yeah.
177 00:36:08.150 ⇒ 00:36:19.639 Uttam Kumaran: Exactly, and also, I think the one piece that we saw is they all struggle with a similar flavor of problems, so every time we go into the next one, we come across as, like, the exact people they need.
178 00:36:19.660 ⇒ 00:36:26.930 Uttam Kumaran: And that’s also, you know, really satisfying. And then our team gets such a wealth of experience, like, we get to work with
179 00:36:26.940 ⇒ 00:36:44.559 Uttam Kumaran: like, we have a pool company that’s a client, we have a flower company, we also have, like, traditional B2B SaaS, home services, like, it’s… and it’s not like we’re… we’re not actually particularly interested in going, like, getting every type of company. I would say where we sort of positioned our business now is that we’re focused on
180 00:36:44.610 ⇒ 00:36:55.880 Uttam Kumaran: as I said, mid-market, at minimum. And then we’re also focused on folks that want to grow, revenue or grow profit, which some companies are not focused entirely on that. They want to cut costs.
181 00:36:55.880 ⇒ 00:37:07.080 Uttam Kumaran: maybe they’re stable or they’re plateauing, like, we want to go for people that they see data as an investment, and that there’s a positive ROI at the end of it. And then same with AI, right? And AI just pulls a lot of that forward.
182 00:37:07.080 ⇒ 00:37:17.219 Uttam Kumaran: for most of the AI agents that we build, we need great data pipelines, we need… it’s mostly, like, the context engineering work is all data and stuff. It’s actually, like, the exact same thing.
183 00:37:17.300 ⇒ 00:37:36.810 Uttam Kumaran: So it’s, like, perfect, because that’s all we do. So, yeah, it’s been good. Yeah, I mean, I think in terms of next steps, I would love to, you know, maybe put you in touch with someone on our team. We have a great project manager that I think would give you some more kind of context about, like, how a project runs, and…
184 00:37:36.810 ⇒ 00:37:40.860 Uttam Kumaran: things like that. I mean, we are a growing company, like, we’re a small company, so…
185 00:37:41.400 ⇒ 00:37:59.319 Uttam Kumaran: it’s a chance to sort of be part of this, but I would say we’ve come from, like, absolutely nothing, so it’s been really interesting that I think our trajectory, especially this year, is looking really, really promising, and we’re trying to bring on folks similar to yourself that can wear multiple hats. I think we’ve struggled in the past where
186 00:37:59.320 ⇒ 00:38:16.989 Uttam Kumaran: I’ve brought on people from industry, but they’re used to just being in, like, one lane, and, you know, we… we may only have a couple engineers on a project, and you have to sort of… the client looks at us like the consultants, and they ask anyone the question, and it’s… it’s actually… you can’t throw it over the…
187 00:38:17.130 ⇒ 00:38:23.640 Uttam Kumaran: you can’t throw it over the fence like you would in a big company, because at that point, that person can’t do anything, right? But…
188 00:38:23.640 ⇒ 00:38:38.310 Uttam Kumaran: In a consultancy, they can immediately go to whoever is signing our check and be like, yo, these guys didn’t support me. And that’s what happens, right? And so, it’s good and bad in several ways, but for us, we’ve never compromised on the quality of our work, like.
189 00:38:38.330 ⇒ 00:38:57.170 Uttam Kumaran: one of the other things we do is, I’m… I try to go survey every tool in every part of the stack, so we have relationships with most of the core vendors, and we don’t take any kickbacks from any of them, so that allows me to go into a client and recommend stuff, and I don’t… I don’t get paid. They usually offer you, like, 10 or 20% of the deal.
190 00:38:57.170 ⇒ 00:39:05.850 Uttam Kumaran: I said, you can keep that. Instead, like, if we like your tool, let’s go do some marketing together, or let’s do a blog post or something that would help both of us.
191 00:39:05.850 ⇒ 00:39:23.100 Uttam Kumaran: And then we… but you’re right, we get to go pick the entire stack for companies, like, we get to decide, like, what the tools they’re using, and explain why, and then they’re usually… they don’t realize the investment that we’re making, and how, when they hire their next data person, how happy that person’s gonna be, that they don’t have, like.
192 00:39:23.180 ⇒ 00:39:24.980 Uttam Kumaran: All these crappy tools, you know?
193 00:39:25.520 ⇒ 00:39:32.040 Shreya Chowdhury: Yeah, and I think that’s great, too, because then it’s also, like, I feel like different companies might have different needs, ….
194 00:39:32.040 ⇒ 00:39:32.720 Uttam Kumaran: Yes.
195 00:39:32.720 ⇒ 00:39:34.610 Shreya Chowdhury: based on what the stack is, so it’s like….
196 00:39:34.610 ⇒ 00:39:55.749 Uttam Kumaran: Like, if you don’t have a lot of analysts, Tableau is fine if you’re just doing executive reports, right? But then if you’re supporting a lot of analysts, maybe we should go for, like, an Omni or a Sigma, or something like that. And so, yeah, we sort of just can choose. But the lovely thing is the vendors need folks like us. So they play ball with us, and then, for me, I’m like, well, why don’t we do a blog post, or…
197 00:39:55.750 ⇒ 00:39:58.699 Uttam Kumaran: Or something where, like, we can promote our business.
198 00:39:58.720 ⇒ 00:40:03.749 Uttam Kumaran: I don’t need your 10% or whatever, and I also don’t want to feel, like, conflicted, so….
199 00:40:03.750 ⇒ 00:40:04.320 Shreya Chowdhury: Yeah.
200 00:40:04.320 ⇒ 00:40:07.739 Uttam Kumaran: You know, and it works out for everybody.
201 00:40:08.110 ⇒ 00:40:23.929 Shreya Chowdhury: Yeah, and I think that’s honestly better, because it’s like, if you have, like, let’s say, like, you do get, like, a kickback from, like, Tableau or, like, whoever it is, then it’s like, you’re going to be more inclined to want to, like, push that onto clients, and I feel like it’s not, like, a one-size-fits-all.
202 00:40:23.930 ⇒ 00:40:24.610 Uttam Kumaran: Definitely.
203 00:40:24.870 ⇒ 00:40:27.260 Shreya Chowdhury: Clients that you are working with.
204 00:40:27.450 ⇒ 00:40:36.479 Uttam Kumaran: But it’s also, like, most consultants, it’s hard to say no to just money that they’re throwing at you, because we’re already gonna implement them, and it may not seem that way, but…
205 00:40:36.480 ⇒ 00:40:47.619 Uttam Kumaran: it’s also a selling point for us, like, when I go to a client, and we have materials and stuff that we share about the tools we recommend, and I’m happy to say, like, yo, we don’t take anything from these guys, so don’t worry about that, like.
206 00:40:47.890 ⇒ 00:40:58.150 Uttam Kumaran: people… and also, people are used to getting really hounded by software vendors these days, and so I want to come in as, like, hey, let us help you make these decisions. We don’t… we’re not paid by anybody but you.
207 00:40:58.200 ⇒ 00:41:14.290 Uttam Kumaran: we only work for you and your problem, so here’s the people that we recommend and why. And then the other thing is we have relationships, so if they need support, or we can get them really great discounts, just because I’ve bought so much software, I know how to, like, get these guys to give pretty heavy discounts, and…
208 00:41:14.290 ⇒ 00:41:23.540 Uttam Kumaran: it works out for them, you know? And so, again, it’s like, it’s just optimizing to do the right thing, and it’s very surprising that that has worked. Versus…
209 00:41:23.540 ⇒ 00:41:38.809 Uttam Kumaran: just, like, trying to make a couple bucks here and there, and for me, it’s just like, can we focus on actually delivering the data work, but also communicating. A lot of internal data teams, they do all this great work, but they do it in, like, an engineering way, where they’re like, oh, we optimize this, we optimize that, but, like.
210 00:41:38.830 ⇒ 00:41:48.820 Uttam Kumaran: still, like, someone in the business is not using data. It’s like, what did we optimize the model for? Like, why did we turn this incremental when someone is still there, like.
211 00:41:49.080 ⇒ 00:41:58.870 Uttam Kumaran: presenting on data that they’re doing in Excel. Like, so there’s… that’s the class of problems that we’re trying to hit, versus I don’t know how… we’re still going kind of far on the technical side.
212 00:41:58.870 ⇒ 00:42:12.539 Uttam Kumaran: But it certainly is much farther on, like, how do we actually get this adopted, and for them to see our ROI? Because for us, if we’re the best data team that they’ve ever seen, and they don’t see a clear path towards, like, replacing us, then we’re there.
213 00:42:12.540 ⇒ 00:42:21.859 Uttam Kumaran: You know, and that’s what makes us a sticky business. And there’s no harm in that, right? Like, all we’re doing is trying to do the best job, and if we stick around because of that, I’m…
214 00:42:22.050 ⇒ 00:42:24.199 Uttam Kumaran: I’m happy, like, that’s great.
215 00:42:25.130 ⇒ 00:42:50.020 Shreya Chowdhury: Yeah, yeah, that… I think that all sounds, like, really great, and I think, like, one of the other things, like, you asked earlier was, like, oh, where do you see yourself going, like, next in your career? And it’s, like, one of the things that you said was, like, yeah, we want people who wear a lot of different hats, like, we’re used to people who, like, are, like, very used to swimming in one lane, and I think, like, that’s something that I want to avoid going forward in my
216 00:42:50.020 ⇒ 00:42:52.710 Shreya Chowdhury: career, like, I was, like, in my next role, I kind of…
217 00:42:52.710 ⇒ 00:42:57.379 Shreya Chowdhury: like, ideally will not be, like, pigeonholed into one place, and I feel like
218 00:42:57.380 ⇒ 00:43:10.059 Shreya Chowdhury: the stuff that you’re talking about is great for, like, a lot of my learning and my experience, too, because I just get to, like, do a little bit of everything and, like, learn a lot more about, like, other, like.
219 00:43:10.160 ⇒ 00:43:12.050 Shreya Chowdhury: things, too. ….
220 00:43:12.050 ⇒ 00:43:28.539 Uttam Kumaran: Yeah, and the reason I ask, you know, is because everybody in our company, like, everybody has a goal in their career, and commonly, I don’t want our company to be another place where someone comes for 2 years and leaves. If you’re gonna do that, that’s fine, I can’t control that, but for me, I want to create a home for people where
221 00:43:28.540 ⇒ 00:43:46.249 Uttam Kumaran: in tech, especially, I think people are used to being like, I gotta go for 2 years and then bounce, because I need, like, my 20%. And for me, I’m like, okay, how do I… as of now that I’m in the position I am, how do I get people to actually want to be at their company? And how do I do things that people didn’t do for me? Which is, one.
222 00:43:46.250 ⇒ 00:44:03.440 Uttam Kumaran: ask me, like, what I want to do, even before, like, people are in the company. Second, it’s actually trying to do my best job to make that reality in any way I can, right? It’s like, for example, we have some people here that want to become managers, and I’m like, okay, well, why don’t you try to manage one person on a team?
223 00:44:03.440 ⇒ 00:44:16.650 Uttam Kumaran: I’ll give you the resources that I learned, or I’ll connect you with managers, or some people want to go deeper technically, okay, let’s go do certifications, or I can get you that type of work that in a… in a company, maybe you’ve taken a year or two.
224 00:44:16.650 ⇒ 00:44:23.339 Uttam Kumaran: But now I’m like, hey, we have a new client starting, it’s this, like, super technical, like, ETL work, like, why don’t I… why don’t you take that on?
225 00:44:23.340 ⇒ 00:44:37.090 Uttam Kumaran: And so for me, I know that the more I can listen and sort of be like, okay, if this person wants to sort of spread, and maybe their goal is like, okay, I could see them maybe helping, like, across the board in different ways, how can I make that a reality?
226 00:44:37.440 ⇒ 00:44:47.570 Uttam Kumaran: Yeah. Because that’s what… that’s what I think is the way to keep people, because I think for us, I don’t know, I think there’s a lot of money in tech, but a lot of people never get, like, fulfilling work.
227 00:44:47.690 ⇒ 00:44:52.270 Uttam Kumaran: Or they go to places that are, like, heavy ego, or a lot of politics, and…
228 00:44:52.380 ⇒ 00:45:02.170 Uttam Kumaran: I don’t know, I don’t want to build a company like that. Like, I don’t like… I didn’t like those people, and they’re not at my company, you know? That’s not the people we’re hiring.
229 00:45:02.540 ⇒ 00:45:17.239 Shreya Chowdhury: Yeah. I… honestly, like, for me, like, yeah, I’ve also heard the thing where it’s, like, every couple years, like, you should jump around and, like, do whatever. I have never really been that type of person. I’m kind of more, like.
230 00:45:17.240 ⇒ 00:45:38.909 Shreya Chowdhury: if I’m, like, I have only had the urge to do that when I’ve been very discontent at my job. I’ve always been like, okay, if there’s reasonable opportunity for, like, career and salary growth, and I’m having fun, that’s, like, my trifecta. I’m perfectly fine where I am. Like, I get complacent, I stay in one place, I’m, like, as long
231 00:45:38.910 ⇒ 00:45:46.409 Shreya Chowdhury: As long as I’m not bored, miserable, or, like, not, like, being paid what I’m, like, what I feel like I’m worth.
232 00:45:46.410 ⇒ 00:45:46.890 Uttam Kumaran: Yeah.
233 00:45:46.890 ⇒ 00:46:00.259 Shreya Chowdhury: I literally just stay in one place, and I’m like, I’m just gonna grow here. Because I… I don’t have, like, a very, like, grass is always greener somewhere else, like, I always believe, like, grass is green where you water it, so I think, like.
234 00:46:00.260 ⇒ 00:46:10.230 Uttam Kumaran: Great. It’s a good… it’s a good way to think about things. I don’t know, it’s tough. I… you know, part of the reason I started the business was because I was like, well, let me just start my own…
235 00:46:10.230 ⇒ 00:46:25.649 Uttam Kumaran: grass over there, you know, and I was really kind of not happy with any of the options, which for me were, like, going back into startups, which I was so kind of, like, burnt out on, and I kind of got a little screwed on the last one, and I’m like, I can’t deal with these people.
236 00:46:25.650 ⇒ 00:46:28.639 Shreya Chowdhury: Our culture is just, like, very different, like.
237 00:46:28.640 ⇒ 00:46:45.070 Uttam Kumaran: Yeah, but I also worked at, like, WeWork, I did some contracting, so the big company stuff, you know, my dad works in… I grew up in the Bay Area, he works in Palo Alto, and I was telling him, like, yeah, maybe I should go to a big company. He’s like, you’re not gonna… you’re gonna kind of probably shoot yourself, like, you’re not gonna like it there either.
238 00:46:45.070 ⇒ 00:46:48.920 Uttam Kumaran: Just because it’s… it’s a… it’s just like, you’ll…
239 00:46:49.170 ⇒ 00:46:58.019 Uttam Kumaran: it’ll take 6 months to get anything done. And I don’t know, this was sort of a third option, which I’ve always been kind of, like, a third option person, like, I… I was in data, and then I.
240 00:46:58.020 ⇒ 00:46:58.940 Shreya Chowdhury: True.
241 00:46:58.940 ⇒ 00:47:18.609 Uttam Kumaran: Yeah, I went into product management, which was… they said, okay, do you want to be an engineering manager? Do you want to stay in IC? And I was like, well, what’s… door number 3 is the worst job, which is product management. But I was like, look, I’ve bought a lot of data tools, I kind of know what I like, I think I can build great data tools for other data people, and this was at Flowcode.
242 00:47:18.610 ⇒ 00:47:29.290 Uttam Kumaran: And I was like, okay, maybe I’ll do that. And that job allowed me to look at, like, how do I run a full-stack team? How do I meet customers? Like, in data, you weren’t… I wasn’t meeting clients and meeting people.
243 00:47:29.290 ⇒ 00:47:39.390 Uttam Kumaran: and building products, and then all of that kind of helped, because now I’m sort of the ultimate multiple hat wearer here, so it’s, it’s kind of an interesting path.
244 00:47:39.870 ⇒ 00:47:52.770 Shreya Chowdhury: Yeah, no, I think that sounds great, and it sounds interesting, and it’s very, like, again, like, it sounds like a fun job, like, you get to, like, help build, like, data foundations for a lot of clients, like, in different
245 00:47:52.920 ⇒ 00:48:04.080 Shreya Chowdhury: fields in different realms, so I think, like, that’s really interesting. As far as, like, yeah, my goals for my… it’s literally just as long as I have reasonable opportunity for, like.
246 00:48:04.520 ⇒ 00:48:10.800 Shreya Chowdhury: career growth, salary growth, and, like, I’m having fun, like, that’s all I’m looking for. I don’t…
247 00:48:10.820 ⇒ 00:48:23.100 Shreya Chowdhury: Yeah, and I think somewhere along the way, things might change, like, I might ask you for, like, hey, I kinda wanna, like, start learning about this, or, like, maybe I might want to shift into this role, but, like, aside from that, I think, like.
248 00:48:23.100 ⇒ 00:48:36.280 Shreya Chowdhury: it will… I see myself mainly working in a space that does leverage data heavily, so it’ll probably likely be something data-related. But that’s kind of all I’m looking for. I feel like working at the big companies, I’ve definitely been, like.
249 00:48:36.960 ⇒ 00:48:43.779 Shreya Chowdhury: In enough times where it’s kind of like you, like, sink through the cracks a little bit because there’s so many, like.
250 00:48:43.780 ⇒ 00:48:44.320 Uttam Kumaran: Yeah.
251 00:48:44.320 ⇒ 00:48:54.490 Shreya Chowdhury: politics, and it’s like, you know, like, there would be, like, cycle after cycle, where it would be like, okay, you’re on track for promotion, you’re on track for promotion. Eventually, like, a year and a half went by.
252 00:48:54.590 ⇒ 00:48:57.679 Uttam Kumaran: That’s so gorgeous.
253 00:48:58.580 ⇒ 00:49:12.230 Shreya Chowdhury: Yeah. And then after a year and a half, I was kind of like, okay, like, it’s like… because we had buy… or, like, we had reviews, like, twice a year, so it’s like, after the fourth cycle, I was kind of like, hmm, like, I don’t really know where to go from here. …
254 00:49:12.690 ⇒ 00:49:16.590 Shreya Chowdhury: And then at some of the smaller roles, it’s like, it’s exactly like you said.
255 00:49:17.420 ⇒ 00:49:27.020 Uttam Kumaran: Yeah, every role is kind of up for grabs, because otherwise, it’s me doing that role, right? So, we have opportunities for people to get
256 00:49:27.020 ⇒ 00:49:37.789 Uttam Kumaran: More involved in, like, delivery, in sales, if you want to, like, manage people, if you want to, like, go do marketing stuff, like, it’s kind of even bigger than…
257 00:49:37.950 ⇒ 00:49:52.129 Uttam Kumaran: than that, where you could go into, like, many different paths in the business in a… in such a risk-averse way. Like, the risk is still on me, and the… and, like, it’s… instead, it’s more of, like, who wants it, and who can go, like, kind of manage
258 00:49:52.130 ⇒ 00:50:00.630 Uttam Kumaran: that, versus, hey, like, we need you to stick in here. It’s… it’s… there’s none of that at all. In fact, I want more people to want to take on more stuff.
259 00:50:00.650 ⇒ 00:50:16.500 Uttam Kumaran: I don’t know who wouldn’t want that, but yeah, for me, that’s… that’s it. Like, we have several engineers that are interested in doing stuff on LinkedIn and marketing stuff. Some people want to come with me to sales calls so they can kind of get a sense of what it’s like to kind of get clients.
260 00:50:17.470 ⇒ 00:50:20.889 Uttam Kumaran: Yeah, and it’s… every day is like a new day in this business, so….
261 00:50:21.660 ⇒ 00:50:36.990 Shreya Chowdhury: Yeah. No, that sounds really cool. It seems like there’s so much more to, like, any role that I would take on, like, if I were to join your team. And I’d be really interested to, like, find out more and see, like, where and how I could fit in. But yeah, I’m…
262 00:50:37.030 ⇒ 00:50:49.529 Shreya Chowdhury: I’m personally open to, like, yeah, figuring out, like, where you have, like, what team and projects you have openings on, and you can see, like, where I might, like, fit in best for you.
263 00:50:49.530 ⇒ 00:50:55.679 Uttam Kumaran: Cool, so let me… maybe as a next step, I’ll… I’ll chat with my team after this, and I’ll get you connected with our…
264 00:50:55.750 ⇒ 00:50:58.810 Uttam Kumaran: I’m a project manager on our team, and you can talk to her.
265 00:50:58.830 ⇒ 00:51:17.680 Uttam Kumaran: I would ask her what it’s like to work with me, what it’s like working at the company, you can ask her whatever. I would actually try to ask her hard questions, so you can kind of get a sense of if I’m just lying the whole time. And then, yeah, and then I’m happy to connect you to someone on the technical team as well.
266 00:51:17.730 ⇒ 00:51:22.809 Uttam Kumaran: Just about, sort of, some of the data work, but I don’t know, I feel like it’s…
267 00:51:22.910 ⇒ 00:51:27.829 Uttam Kumaran: I asked you several questions, like, I feel like you kind of get the sense it’s a lot of the same stuff.
268 00:51:28.860 ⇒ 00:51:32.620 Uttam Kumaran: And so, and then, yeah, I think maybe chat with her, and then we can kind of go from there.
269 00:51:33.360 ⇒ 00:51:34.780 Shreya Chowdhury: Cool, sounds great.
270 00:51:35.310 ⇒ 00:51:39.719 Uttam Kumaran: Okay, perfect. Well, thanks, Shreya, for the time, appreciate it. And then, yeah, we’ll be in touch this week.
271 00:51:40.110 ⇒ 00:51:41.720 Shreya Chowdhury: Alright, sounds good. Thank you so much.
272 00:51:41.720 ⇒ 00:51:43.240 Uttam Kumaran: Okay, thank you, bye.