Meeting Title: BrainPost Data Engineer Interview Date: 2026-04-09 Meeting participants: Achyut Sridhar Kulkarni, Kaela Gallagher
WEBVTT
1 00:01:33.590 ⇒ 00:01:35.410 Kaela Gallagher: Hi, how’s it going?
2 00:01:35.680 ⇒ 00:01:38.310 Achyut Sridhar Kulkarni: Hey, good afternoon. Oh, is it good morning?
3 00:01:38.310 ⇒ 00:01:44.180 Kaela Gallagher: Good afternoon, thanks for taking some time to meet with me, appreciate it.
4 00:01:44.180 ⇒ 00:01:45.389 Achyut Sridhar Kulkarni: Yeah, absolutely.
5 00:01:45.390 ⇒ 00:01:57.080 Kaela Gallagher: Yeah, I think you had maybe, like, interacted with our… our post about our open positions, but yeah, just wanted to reach out and, like, learn a little bit more about you, and
6 00:01:57.200 ⇒ 00:02:01.610 Kaela Gallagher: Yeah, curious, like, what is making you interested in a new position?
7 00:02:02.540 ⇒ 00:02:10.730 Achyut Sridhar Kulkarni: Yeah, so, a bit about myself, to start with. So, I’m currently working as a founding engineer at a stealth startup.
8 00:02:10.900 ⇒ 00:02:21.509 Achyut Sridhar Kulkarni: Where I’m designing, their entire database architecture. so it’s a small, social networking platform, which is location-based.
9 00:02:21.610 ⇒ 00:02:38.049 Achyut Sridhar Kulkarni: If you are familiar with, meetup.com, that’s something that, we are targeting to be our competition. So, I’m currently designing, the database architecture where I’m building MongoDB.
10 00:02:38.100 ⇒ 00:02:44.159 Achyut Sridhar Kulkarni: Neo4j and GCP for, entire end-to-end database,
11 00:02:44.860 ⇒ 00:02:50.470 Achyut Sridhar Kulkarni: To capture and maintain user data and relationship among them.
12 00:02:50.660 ⇒ 00:03:09.680 Achyut Sridhar Kulkarni: So, I’m building a knowledge graph, using Neo4J to capture relationship and interaction between individual users, the events that they might be interested in, and I’m currently working on building a recommendation system on top of this knowledge graph.
13 00:03:09.800 ⇒ 00:03:15.700 Achyut Sridhar Kulkarni: Where, which will help, users, connect with one another. And,
14 00:03:15.840 ⇒ 00:03:19.810 Achyut Sridhar Kulkarni: Hopefully, to show them events that they’ll be interested in attending.
15 00:03:19.970 ⇒ 00:03:37.800 Achyut Sridhar Kulkarni: So that’s what I’m currently working on, and before this, I started my career at another startup called Make Computing as a data scientist, where I worked on video analytics solutions, interacting with clients on a day-to-day basis, spinning up a quick POC for them.
16 00:03:37.910 ⇒ 00:03:44.209 Achyut Sridhar Kulkarni: Gathering feedback, for the POC, and building products on top of that.
17 00:03:44.210 ⇒ 00:04:00.849 Achyut Sridhar Kulkarni: So that was my day-to-day, at my computing. I was there for around 3 years, which led me to my Master’s in data science. I graduated, in last year, May, from Rates Institute of Technology with a 3.9 GPA.
18 00:04:00.930 ⇒ 00:04:14.150 Achyut Sridhar Kulkarni: Where I worked, my capstone project was working with Toyota Research Institute and a couple of universities, which were University of Florida and UCI Irvine.
19 00:04:14.230 ⇒ 00:04:21.410 Achyut Sridhar Kulkarni: Where, I worked on building an explainable AI method, for autonomous vehicles.
20 00:04:21.890 ⇒ 00:04:33.310 Achyut Sridhar Kulkarni: So, the problem that Toyota was facing was that their autonomous vehicle was not able to differentiate between actual human beings and posters or banners that are out there on the roads.
21 00:04:33.410 ⇒ 00:04:39.379 Achyut Sridhar Kulkarni: So, I helped them understand why exactly that behavior was…
22 00:04:39.510 ⇒ 00:04:45.290 Achyut Sridhar Kulkarni: Seen in their underlying neural network models that they were using for autonomous vehicles.
23 00:04:45.510 ⇒ 00:04:58.409 Achyut Sridhar Kulkarni: So that was an incentive project that I did. It lasted for around one year during my master’s, and yeah, I’m looking for opportunities currently where I can work with,
24 00:04:58.410 ⇒ 00:05:09.540 Achyut Sridhar Kulkarni: you know, forward-facing clients, where I can understand their needs, build them products that will help them solve real-world problems.
25 00:05:10.170 ⇒ 00:05:26.499 Achyut Sridhar Kulkarni: Also, I’m looking for collaboration with a set of team members that I can interact with, you know, pitch some ideas, bounce some ideas off them, collaborate on engineering, and,
26 00:05:26.600 ⇒ 00:05:41.820 Achyut Sridhar Kulkarni: data science… data part of the job. So, that… that led me to my application with BrainPost. I saw the CEO’s post, it was quite intriguing. I went through the website, and I just thought of reaching out to him.
27 00:05:42.440 ⇒ 00:05:45.749 Kaela Gallagher: Okay, okay, great.
28 00:05:46.410 ⇒ 00:05:56.339 Kaela Gallagher: Thank you for kind of, like, walking me through your experience there. I know you mentioned using Neo4J, but curious, like, what else you would consider part of your tech stack?
29 00:05:57.140 ⇒ 00:06:05.160 Achyut Sridhar Kulkarni: Yeah, so, as I mentioned, in my current work, my tech stack is MongoDB, Neo4j, and Google Cloud Platform.
30 00:06:05.250 ⇒ 00:06:17.250 Achyut Sridhar Kulkarni: I regularly use MongoDB to track and store user data that they, they provide us while registering for the application.
31 00:06:17.250 ⇒ 00:06:36.789 Achyut Sridhar Kulkarni: Moving forward, once they register and the data is in Neo4J, I make use of that data to build sort of a knowledge graph, connecting every user with one another based on… based on their interests, their, their interaction with the platform, the events that they want to go to.
32 00:06:36.830 ⇒ 00:06:42.810 Achyut Sridhar Kulkarni: So this knowledge graph helps in, sort of building a recommendation system.
33 00:06:43.230 ⇒ 00:06:51.359 Achyut Sridhar Kulkarni: That will, you know, help us populate their feed with the events that they’ll be interested in, so to keep them engaged in the platform.
34 00:06:51.790 ⇒ 00:07:02.879 Achyut Sridhar Kulkarni: Also, there is an aspect where a lot of these events have, you know, social media posting about images that they share during the events, or…
35 00:07:02.880 ⇒ 00:07:12.199 Achyut Sridhar Kulkarni: images that users share, among themselves, right? So in order to store these images and videos, I’m making use of Google Cloud Platform.
36 00:07:12.530 ⇒ 00:07:14.700 Kaela Gallagher: Okay. Okay, great. Have you…
37 00:07:14.700 ⇒ 00:07:22.290 Achyut Sridhar Kulkarni: And everything is built on Python, so Python is my primary language that I have been working with for around…
38 00:07:22.640 ⇒ 00:07:23.870 Achyut Sridhar Kulkarni: 6 years now.
39 00:07:24.160 ⇒ 00:07:29.700 Kaela Gallagher: Okay. Have you used, like, Snowflakes, or Databricks, or, like, a similar tool?
40 00:07:30.060 ⇒ 00:07:41.470 Achyut Sridhar Kulkarni: Yeah, absolutely. So, I have worked on multiple projects, using, Snowflake and DataBlack. I recently worked on a data engineering project where
41 00:07:41.520 ⇒ 00:07:53.800 Achyut Sridhar Kulkarni: I built an end-to-end ETL platform for data ingestion. I made use of these tools in my previous experience as well at my computing, where
42 00:07:53.800 ⇒ 00:08:08.560 Achyut Sridhar Kulkarni: you know, we were streaming video data, on edge devices, so AWS was our go-to cloud platform back then, so I made use of AWS to make sure, video streaming is seamless.
43 00:08:09.080 ⇒ 00:08:11.830 Kaela Gallagher: Okay, and what about DBT?
44 00:08:12.720 ⇒ 00:08:26.850 Achyut Sridhar Kulkarni: I do not have, professional experience in dbt, but I have, I have learned about it, and, I’m just waiting for an opportunity to make use of what I’ve learned.
45 00:08:27.390 ⇒ 00:08:30.799 Kaela Gallagher: Okay, okay, awesome. Where are you currently based?
46 00:08:31.200 ⇒ 00:08:33.150 Achyut Sridhar Kulkarni: I’m currently in Chicago, Illinois.
47 00:08:33.380 ⇒ 00:08:41.620 Kaela Gallagher: Oh, okay, okay, cool. Are you open to, like, relocating in the future, or do you see yourself in Chicago for a while?
48 00:08:41.620 ⇒ 00:08:45.670 Achyut Sridhar Kulkarni: No, absolutely, I’m, absolutely open to relocation.
49 00:08:45.670 ⇒ 00:08:50.880 Kaela Gallagher: Okay, okay. And what about, compensation? Like, what’s the range you’re targeting there?
50 00:08:51.110 ⇒ 00:09:03.560 Achyut Sridhar Kulkarni: Yeah, so, I’m looking… what I’m looking for is roles and responsibilities in the role currently. Given the right roles and responsibilities, I’m open to discussing, the compensation part of the
51 00:09:03.560 ⇒ 00:09:11.489 Achyut Sridhar Kulkarni: job, so I’d rather you tell me, what’s the budget that you guys, have for this role.
52 00:09:11.810 ⇒ 00:09:17.359 Kaela Gallagher: Yeah, yeah, just to give you an overview, I know you mentioned, like, roles and responsibilities.
53 00:09:17.370 ⇒ 00:09:42.229 Kaela Gallagher: So, just an overview of kind of what we do and what’s most important to us as we’re searching for a data engineer. So, we do data and AI consulting. We work with a lot of small to mid-sized companies, and we offer 3 different service lines. One is data, one is AI, and one is strategy and analytics, and oftentimes we have, like, a blend of those three teams supporting clients.
54 00:09:42.720 ⇒ 00:09:46.649 Kaela Gallagher: But obviously this data engineer role would sit within our data team.
55 00:09:46.960 ⇒ 00:10:04.820 Kaela Gallagher: The most important things to us would be, somebody that can context switch really easily. You would likely be supporting two to three clients at a time, maybe using different tooling for each of them, and so somebody that’s able to be adaptable and jump back and forth is really important.
56 00:10:04.850 ⇒ 00:10:20.149 Kaela Gallagher: And then, because we are a smaller organization, still about 25 people, all of our engineers are still joining calls with clients, so somebody that has interacted with clients before would be important to us as well.
57 00:10:20.160 ⇒ 00:10:39.300 Kaela Gallagher: Right now, our entire organization is on a 1099 basis, so independent contracting. So, in terms of pay, we would be looking at, like, hourly rates, and that would be the total compensation for now.
58 00:10:39.330 ⇒ 00:10:44.760 Kaela Gallagher: So, just wanted to kind of give an overview of that. Do you have any questions?
59 00:10:44.860 ⇒ 00:10:45.400 Kaela Gallagher: For me?
60 00:10:45.400 ⇒ 00:10:59.240 Achyut Sridhar Kulkarni: Yeah, I mean, what kind of clients are you targeting, and what’s the major… because of all the AI technologies that are coming out, what’s the one product that every client is looking for nowadays?
61 00:10:59.480 ⇒ 00:11:12.120 Kaela Gallagher: Mmm, yeah, in terms of our client base, like I mentioned, small to mid-size, we have a lot of, like, e-com and, like, CPG brands that we work with, so, like.
62 00:11:12.380 ⇒ 00:11:30.009 Kaela Gallagher: brands that you would find on the shelf at, like, a Target or a Walmart. We have, like, a healthcare client that we work with, we have, like, B2B and, like, SaaS clients. I think we have, like, a financial client as well, so, kind of across the spectrum, for sure.
63 00:11:30.410 ⇒ 00:11:40.939 Achyut Sridhar Kulkarni: Yeah, and you mentioned it’s just me, it’s a small team of 25 that collaborate, right? So, will… will there be an aspect where…
64 00:11:40.990 ⇒ 00:11:50.459 Achyut Sridhar Kulkarni: Someone coming into this role, visits client site and, helps them on their location, or will that be done remotely?
65 00:11:51.000 ⇒ 00:11:56.369 Kaela Gallagher: So our team is fully remote. We have team members actually across the world.
66 00:11:56.380 ⇒ 00:12:14.230 Kaela Gallagher: So yeah, everything we do is done remotely. The reason I asked about relocation is because we do have quite a few people now in LA and Austin, so we kind of have these, like, hubs popping up, so if people are open to relocating to one of those hubs.
67 00:12:14.380 ⇒ 00:12:24.830 Kaela Gallagher: that’s a plus for us, just because, like, I live in LA, and we all just get together, like, once a week, and co-work together, so it’s… it’s a huge bonus for us, for sure.
68 00:12:24.950 ⇒ 00:12:36.760 Achyut Sridhar Kulkarni: Yeah, absolutely. I mean, working with team members, going to office, I think that’s the fun part of corporate jobs, so… Yeah. Yeah. Yeah, so,
69 00:12:36.760 ⇒ 00:12:45.789 Achyut Sridhar Kulkarni: What do you think, success, defines success for someone in this role for, let’s say, 6 months? What…
70 00:12:46.050 ⇒ 00:12:52.030 Achyut Sridhar Kulkarni: Should someone coming into this role should have achieved by the end of 6 months to term it as success.
71 00:12:52.370 ⇒ 00:12:59.270 Kaela Gallagher: Yeah, I think for us, because we are small and we move really quickly, like.
72 00:12:59.780 ⇒ 00:13:08.630 Kaela Gallagher: The organization will look really different in 6 months, so when we talk about what success looks like, we’re probably looking at, like, the first 30 days.
73 00:13:08.630 ⇒ 00:13:09.410 Achyut Sridhar Kulkarni: Okay.
74 00:13:09.550 ⇒ 00:13:18.929 Kaela Gallagher: So, yeah, we move really quickly, and I think it’s all about, like, just getting ramped up really quickly. And then also, just, like.
75 00:13:19.080 ⇒ 00:13:37.210 Kaela Gallagher: staying very open to new ideas. We build a lot of internal tooling for ourself as well, and I think our platform team is probably rolling out something new and exciting, like, every week. So, staying up to date with all of our, like, internal improvements, I would say, is super important as well.
76 00:13:38.180 ⇒ 00:13:46.709 Achyut Sridhar Kulkarni: Yeah, absolutely, that sounds wonderful. What will be the hiring timeline, and what will be the rounds involved in hiring?
77 00:13:47.280 ⇒ 00:14:01.470 Kaela Gallagher: Yeah, so I’m chatting with quite a few people this week, so I’ll be partnering with, like, the engineering team and the hiring managers for this role to kind of review all of the candidates, and then decide who to move forward to interviews.
78 00:14:01.470 ⇒ 00:14:17.419 Kaela Gallagher: Once we have candidates move to interviews, we have 3 rounds. So the first one is more about your experience overall, second one is a little bit more technical, and the third one, we give you, like, a take-home challenge, and then you bring your solution to, like, the final panel.
79 00:14:17.420 ⇒ 00:14:32.899 Kaela Gallagher: So that’s how it’s structured. For each round, we send you, like, a booking link, so you can choose a time that works for you. So, you know, if you’re booking interviews pretty quickly, like, within the next couple days, I would say we can complete the process within a couple weeks.
80 00:14:33.860 ⇒ 00:14:39.049 Achyut Sridhar Kulkarni: Yeah, that sounds great. Yeah, those are the questions I had. If you have anything, please.
81 00:14:39.590 ⇒ 00:14:46.379 Kaela Gallagher: Yeah, I don’t have anything else for you. Yeah, it was great getting to know you, and just really appreciate your time.
82 00:14:46.900 ⇒ 00:14:53.989 Achyut Sridhar Kulkarni: Yeah, it was great, getting to know about the team, what you guys are working on, and I really look forward to the next steps, yeah.
83 00:14:53.990 ⇒ 00:14:57.010 Kaela Gallagher: Okay, awesome, thank you so much, have a good one.
84 00:14:57.010 ⇒ 00:14:58.739 Achyut Sridhar Kulkarni: You too, have a great day.
85 00:14:58.740 ⇒ 00:15:00.129 Kaela Gallagher: Thanks, bye.