Meeting Title: Brainforge Analytics Engineer Interview Date: 2026-02-20 Meeting participants: Johnathan Reyna, Johnathan’s Notetaker (Otter.ai), Awaish Kumar
WEBVTT
1 00:03:34.060 ⇒ 00:03:34.950 Johnathan Reyna: Hello?
2 00:03:41.460 ⇒ 00:03:42.999 Awaish Kumar: Hi, how are you doing?
3 00:03:43.390 ⇒ 00:03:44.370 Johnathan Reyna: Good, how are you?
4 00:03:45.130 ⇒ 00:03:50.849 Awaish Kumar: I’m good. Hi, my name is Arish Kumar, and…
5 00:03:51.200 ⇒ 00:03:55.709 Awaish Kumar: Today’s… in today’s interview, actually, we are just going to talk about,
6 00:03:56.520 ⇒ 00:04:03.019 Awaish Kumar: A little bit about Brainforge, what the company does, and then we are more going to talk about your…
7 00:04:03.330 ⇒ 00:04:06.390 Awaish Kumar: Experience, and the kind of projects you’ve worked on.
8 00:04:06.730 ⇒ 00:04:07.330 Johnathan Reyna: Sure.
9 00:04:08.900 ⇒ 00:04:13.929 Awaish Kumar: Starting with, myself, I’m a data engineer, I lead…
10 00:04:14.050 ⇒ 00:04:17.099 Awaish Kumar: data engineering department here in Brainford.
11 00:04:17.790 ⇒ 00:04:26.010 Awaish Kumar: And, Brentford mostly… Like, Brentford provides data and AI consultancy services.
12 00:04:26.460 ⇒ 00:04:32.110 Awaish Kumar: To the clients from, mostly from the US, and
13 00:04:32.410 ⇒ 00:04:37.230 Awaish Kumar: Brainford targets, like, mid to large-scale enterprises.
14 00:04:37.860 ⇒ 00:04:56.879 Awaish Kumar: And, yeah, and it operates completely remotely, so we have employees from across the world, including, like, US, Europe, Asia, and Asia also, like, India, Pakistan, Philippines. So we have people from across the world, and normally we work through Slack.
15 00:04:57.160 ⇒ 00:05:02.190 Awaish Kumar: and Notion pages, like, there’s a lot of async communication and documentation.
16 00:05:02.620 ⇒ 00:05:06.129 Awaish Kumar: So, that’s the mode of communication in the company.
17 00:05:06.300 ⇒ 00:05:15.370 Awaish Kumar: And yeah, that’s mostly it about Brainforge. We can start with your introduction, and then we can maybe talk more about
18 00:05:15.730 ⇒ 00:05:17.150 Awaish Kumar: your experiences.
19 00:05:17.490 ⇒ 00:05:18.120 Johnathan Reyna: True.
20 00:05:18.220 ⇒ 00:05:23.760 Johnathan Reyna: Yeah, and let me start by apologizing. My wife went to the emergency room, so I had to…
21 00:05:23.930 ⇒ 00:05:29.579 Johnathan Reyna: I missed our first, scheduled interview, so I apologize for that, and I appreciate the,
22 00:05:29.650 ⇒ 00:05:41.159 Johnathan Reyna: the willingness to allow me to move it and still, attend it. So my background, I’m prior service marine. I didn’t do anything technical.
23 00:05:41.190 ⇒ 00:05:50.499 Johnathan Reyna: The most technical thing I did there was communications, and I worked in the infantry. I did some supply chain logistics management for a reconnaissance unit.
24 00:05:50.830 ⇒ 00:05:57.390 Johnathan Reyna: And then after that, I went back to school, for management science, so…
25 00:05:57.510 ⇒ 00:06:14.870 Johnathan Reyna: supply chain optimization, when I got out of the Marine Corps, and, started working at USAA for some number of years as a software developer, as a data science analyst, and then also,
26 00:06:15.440 ⇒ 00:06:22.309 Johnathan Reyna: as a, program project manager for, a large IT team.
27 00:06:22.650 ⇒ 00:06:25.339 Johnathan Reyna: Across the Consumer Lending Department.
28 00:06:25.660 ⇒ 00:06:31.090 Johnathan Reyna: Recently I’ve been with Booz Allen for about 3 years, where I’ve done a variety of things for,
29 00:06:31.560 ⇒ 00:06:40.089 Johnathan Reyna: From servicing, various, Department of War organizations, like the Air Force and
30 00:06:40.520 ⇒ 00:06:51.220 Johnathan Reyna: the Navy, some Marine Corps, but primarily focus on solution architecture for, deploying advanced technologies in cyberspace, so…
31 00:06:51.340 ⇒ 00:07:00.139 Johnathan Reyna: Using AI, ML, and things like that, and developing solutions within cybersecurity and in that environment.
32 00:07:01.080 ⇒ 00:07:01.690 Awaish Kumar: Okay.
33 00:07:03.150 ⇒ 00:07:06.990 Awaish Kumar: Okay, and then I see that you have applied for…
34 00:07:07.110 ⇒ 00:07:11.029 Awaish Kumar: Analytics engineer role here at Brainford.
35 00:07:11.140 ⇒ 00:07:20.620 Awaish Kumar: So, I would like to… Understand how your current skills or experiences, match with the Sure.
36 00:07:20.900 ⇒ 00:07:24.859 Johnathan Reyna: Yeah, so, in my role, I do a variety of different,
37 00:07:25.250 ⇒ 00:07:33.010 Johnathan Reyna: Activities from developing proof of concepts for, reporting requirements, across.
38 00:07:33.150 ⇒ 00:07:46.520 Johnathan Reyna: a variety of different, needs, so sometimes it’s leadership dashboarding that’s a need, all the way down to, developing the business rules behind, creating a view for,
39 00:07:46.730 ⇒ 00:07:51.379 Johnathan Reyna: Extracting and loading data into a new org… a new location.
40 00:07:51.560 ⇒ 00:07:56.390 Johnathan Reyna: So, I’ve done visualizations on a variety of different platforms.
41 00:07:56.550 ⇒ 00:08:03.830 Johnathan Reyna: from, Tableau to… through Python, while also using, other,
42 00:08:04.330 ⇒ 00:08:11.050 Johnathan Reyna: I would say out-of-the-box softwares that have analytical capabilities, embedded in them.
43 00:08:11.770 ⇒ 00:08:17.790 Johnathan Reyna: And then a lot of the visualizations that we do are,
44 00:08:19.780 ⇒ 00:08:32.530 Johnathan Reyna: I would say they’re… they’re role-based, i.e, I don’t need a senior executive to see a dashboard that is needed for an operational manager, on, on,
45 00:08:32.740 ⇒ 00:08:33.979 Johnathan Reyna: On mission side.
46 00:08:35.970 ⇒ 00:08:41.520 Awaish Kumar: Okay, so… I mean, you have experience with the DBT?
47 00:08:42.679 ⇒ 00:08:44.689 Johnathan Reyna: with, dbt, what do you mean?
48 00:08:45.260 ⇒ 00:08:52.450 Awaish Kumar: Dbt is a tool, for transforming the… Data, like, in… in databases.
49 00:08:54.570 ⇒ 00:08:56.769 Johnathan Reyna: I don’t know what the… the acronym, I’m sorry.
50 00:08:56.770 ⇒ 00:08:57.700 Awaish Kumar: Noise!
51 00:08:57.830 ⇒ 00:09:03.969 Awaish Kumar: It’s a tool, it’s the name of the tool, DBT. Not an acronym, it’s called DBT.
52 00:09:03.970 ⇒ 00:09:05.110 Johnathan Reyna: No.
53 00:09:05.130 ⇒ 00:09:15.709 Awaish Kumar: normally the, I think, data build tool, what they call themselves, but famous by dbt, but that’s okay. That was just a question that came to my mind, because…
54 00:09:16.070 ⇒ 00:09:18.810 Awaish Kumar: Most of the transformations right now
55 00:09:19.020 ⇒ 00:09:25.900 Awaish Kumar: happens using that tool, because this is… this is just writing SQL, nothing fancy, but it’s more like a…
56 00:09:26.100 ⇒ 00:09:29.550 Awaish Kumar: way to version control your SQL changes.
57 00:09:29.700 ⇒ 00:09:30.500 Johnathan Reyna: Sure.
58 00:09:30.620 ⇒ 00:09:36.510 Awaish Kumar: In some way. Okay, then my next question would be, then, why, like,
59 00:09:36.870 ⇒ 00:09:38.769 Awaish Kumar: While you are leaving your control.
60 00:09:42.100 ⇒ 00:09:50.080 Johnathan Reyna: just… I mean, a lot of the challenges that the Department of War is facing impact, how projects move.
61 00:09:50.270 ⇒ 00:09:54.170 Johnathan Reyna: So, a lot of, changes are…
62 00:09:54.290 ⇒ 00:10:02.200 Johnathan Reyna: Currently in our industry, so I’m looking to change into an industry that I think has the upward growth.
63 00:10:03.770 ⇒ 00:10:09.109 Awaish Kumar: Okay, fine, hmm, okay, can we talk about…
64 00:10:09.850 ⇒ 00:10:13.710 Awaish Kumar: Any one of the projects, where you have been hands-on.
65 00:10:13.910 ⇒ 00:10:18.100 Awaish Kumar: And that, that delivered, like, end-to-end.
66 00:10:18.420 ⇒ 00:10:19.830 Johnathan Reyna: Sure, so…
67 00:10:20.510 ⇒ 00:10:29.839 Johnathan Reyna: I would say the latest one was, supporting the Department of the Navy. They had 17 disparate data sources.
68 00:10:30.090 ⇒ 00:10:36.589 Johnathan Reyna: So, establishing connections to those 17 data sources, and then…
69 00:10:36.730 ⇒ 00:10:44.109 Johnathan Reyna: developing an extract capability, i.e, whether it’s an API or, it’s a manual pull or an automated.
70 00:10:44.270 ⇒ 00:10:48.299 Johnathan Reyna: Pool using, a variety of different means.
71 00:10:48.450 ⇒ 00:10:55.819 Johnathan Reyna: So, developing those Python scripts to put them into the external data loader for a cloud environment.
72 00:10:55.940 ⇒ 00:10:58.109 Johnathan Reyna: That’s proprietary to my company.
73 00:10:58.320 ⇒ 00:11:16.410 Johnathan Reyna: Where we moved the data from that extracted point, and then did our transformations, in the data loader, and then pushed the data to an S3, bucket, and then, used a Tableau, server to, create and, maintain.
74 00:11:16.560 ⇒ 00:11:22.360 Johnathan Reyna: Public dashboards that we would publish for consumption.
75 00:11:23.040 ⇒ 00:11:30.279 Awaish Kumar: So, I mean, how that powerful pipeline was set up, like, what you did to ingest data from those 17…
76 00:11:31.170 ⇒ 00:11:37.819 Johnathan Reyna: Yeah, so, sure. So, and it depends… each one was a little bit different,
77 00:11:38.180 ⇒ 00:11:48.060 Johnathan Reyna: Some were, no kidding, we would have to get, due to classifications and sensitivity of data, we would have to get secure,
78 00:11:48.260 ⇒ 00:11:53.030 Johnathan Reyna: Secure Mail, which is a… a,
79 00:11:54.320 ⇒ 00:11:58.879 Johnathan Reyna: It’s almost like an FTP, but through Outlook, really, is what it kind of boils down to.
80 00:11:58.880 ⇒ 00:11:59.780 Awaish Kumar: Yeah, okay.
81 00:11:59.780 ⇒ 00:12:08.420 Johnathan Reyna: And so, in some formats, we would get, no kidding, Excel spreadsheets, and then some were,
82 00:12:08.740 ⇒ 00:12:13.439 Johnathan Reyna: A lot of them started off with Excel spreadsheets that we would use.
83 00:12:13.640 ⇒ 00:12:21.650 Johnathan Reyna: And then we would ultimately establish that, data table in our,
84 00:12:21.650 ⇒ 00:12:25.410 Awaish Kumar: So, I mean, you receive those files?
85 00:12:25.410 ⇒ 00:12:27.430 Johnathan Reyna: Sure. Your Excel files.
86 00:12:28.510 ⇒ 00:12:34.949 Awaish Kumar: How did you receive it? Through an email, like, maybe using a secure mail, but then how were you…
87 00:12:35.150 ⇒ 00:12:39.799 Awaish Kumar: basically, like, how did you automate it there? Like, from the email, how did you.
88 00:12:39.800 ⇒ 00:12:40.530 Johnathan Reyna: Yeah.
89 00:12:40.530 ⇒ 00:12:42.890 Awaish Kumar: file, and how to then move it.
90 00:12:43.150 ⇒ 00:12:58.769 Johnathan Reyna: So we would sometimes… well, when we could, we would create a service account on the database with the DBAs, if there was a DBA. Some of the data sources, because of the way it’s collected, they didn’t have databases that would maintain historical data.
91 00:12:58.920 ⇒ 00:13:04.899 Johnathan Reyna: And then actually some of the databases were not ours. They were, other contractors.
92 00:13:05.030 ⇒ 00:13:09.300 Johnathan Reyna: So sometimes, and I would say,
93 00:13:11.140 ⇒ 00:13:14.009 Johnathan Reyna: About 9 of the data sources we couldn’t automate.
94 00:13:14.240 ⇒ 00:13:20.349 Johnathan Reyna: Because the… We didn’t own…
95 00:13:20.920 ⇒ 00:13:28.969 Johnathan Reyna: the ability to establish and develop the API that we would need, and they then have the skill set to develop.
96 00:13:29.160 ⇒ 00:13:32.929 Johnathan Reyna: the API capability for us to connect to, or leverage.
97 00:13:33.050 ⇒ 00:13:36.700 Johnathan Reyna: But the ones that we were able to work with.
98 00:13:36.860 ⇒ 00:13:49.400 Johnathan Reyna: the database owners either had API capabilities, they just weren’t being used, so we would ultimately create those, service accounts on the databases, and then, and just use API calls.
99 00:13:49.410 ⇒ 00:13:57.909 Johnathan Reyna: Where else we couldn’t, and then we would pull the data into our EDL. For the ones that were manual, we created, Python scripts.
100 00:13:57.980 ⇒ 00:14:02.309 Johnathan Reyna: That we would execute, Once we get the file.
101 00:14:02.520 ⇒ 00:14:16.570 Johnathan Reyna: To automatically just take the Excel spreadsheet and dump it into our storage location, and then, pipe over from our, our localized, database, or our data…
102 00:14:16.700 ⇒ 00:14:19.129 Johnathan Reyna: location are,
103 00:14:20.000 ⇒ 00:14:25.940 Johnathan Reyna: Because it was on a localized server, and then we would push that over to our ETL, or our EDL.
104 00:14:26.780 ⇒ 00:14:36.020 Awaish Kumar: Okay, like, I mean, you mentioned that you wrote some Python script to get… to make some API calls to retrieve the data, so how,
105 00:14:36.230 ⇒ 00:14:38.349 Awaish Kumar: those Python scripts were deployed.
106 00:14:42.740 ⇒ 00:14:45.080 Johnathan Reyna: As far as,
107 00:14:48.360 ⇒ 00:14:49.460 Johnathan Reyna: You mean…
108 00:14:49.630 ⇒ 00:14:56.639 Johnathan Reyna: like, when we were running those Python scripts locally on our… on our devices to ultimately extract and push that data, I mean…
109 00:14:56.980 ⇒ 00:14:59.210 Johnathan Reyna: They were just writing the scripts themselves.
110 00:14:59.460 ⇒ 00:15:01.690 Awaish Kumar: That is… that is a manual process.
111 00:15:01.920 ⇒ 00:15:02.480 Johnathan Reyna: Right.
112 00:15:03.070 ⇒ 00:15:15.860 Awaish Kumar: Right, but when you are saying that if there is an API, you wrote in a script that the Python script can read using the API, you are trying to automate the process so that Python script needs to run
113 00:15:16.690 ⇒ 00:15:21.490 Awaish Kumar: Automatically, right? We don’t have to go in and trigger that Python one manually.
114 00:15:21.880 ⇒ 00:15:29.730 Johnathan Reyna: Yeah, they didn’t have any, so before, I’ve used, applications like, Control-M and things like that to develop.
115 00:15:29.860 ⇒ 00:15:33.139 Johnathan Reyna: Truly automated,
116 00:15:33.420 ⇒ 00:15:41.379 Johnathan Reyna: ETL pipelines. Unfortunately, we didn’t have access because of the secure environments. We didn’t have any ATO,
117 00:15:41.900 ⇒ 00:15:47.660 Johnathan Reyna: applications, everything was still manual to the point of we had to implement or execute the code itself.
118 00:15:48.020 ⇒ 00:15:48.960 Johnathan Reyna: Locally.
119 00:15:49.580 ⇒ 00:16:00.699 Awaish Kumar: And then, how would you, for example, that’s a different question than this. So, if in your project, you are working on something, and then if there is a…
120 00:16:00.980 ⇒ 00:16:08.720 Awaish Kumar: conflict, between the team members. How would you then respond?
121 00:16:08.890 ⇒ 00:16:14.520 Johnathan Reyna: Yeah, so, we had a primary point of contact for each data source, so if there was…
122 00:16:14.630 ⇒ 00:16:20.759 Johnathan Reyna: Any issue, either we didn’t receive the file, or when we did our file, comparison, or,
123 00:16:20.880 ⇒ 00:16:31.950 Johnathan Reyna: validation on row… whatever we were using for the control for the data that we were receiving. If it was incorrect, it would trigger, a notification to us.
124 00:16:32.090 ⇒ 00:16:37.479 Johnathan Reyna: Once we pushed it to EDL, And so, it happened…
125 00:16:38.250 ⇒ 00:16:48.330 Johnathan Reyna: I don’t know, every couple weeks, some of the data owners would change the file structures, change column names, or something like that, so our scripts wouldn’t execute correctly.
126 00:16:48.450 ⇒ 00:16:50.610 Johnathan Reyna: So we would connect with the…
127 00:16:50.900 ⇒ 00:16:56.689 Johnathan Reyna: the, data owners… I say we, but I would connect with the data owners and say, you know.
128 00:16:57.240 ⇒ 00:17:01.469 Johnathan Reyna: Like, what’d you guys change? And they usually don’t notify us until afterwards anyway.
129 00:17:01.690 ⇒ 00:17:06.589 Johnathan Reyna: And then we would make the changes, and then rerun, the push…
130 00:17:07.000 ⇒ 00:17:09.999 Awaish Kumar: Okay, it seems that is just kind of a…
131 00:17:10.480 ⇒ 00:17:18.970 Awaish Kumar: They push something without notifying you, but my point is more like, if you have conflict, for example, you are working on a project.
132 00:17:19.220 ⇒ 00:17:23.349 Awaish Kumar: You came up with a plan, or you architected a solution.
133 00:17:23.569 ⇒ 00:17:27.620 Awaish Kumar: But while you are, for example, few team members.
134 00:17:27.859 ⇒ 00:17:29.980 Awaish Kumar: On the projects, and you…
135 00:17:31.730 ⇒ 00:17:37.909 Awaish Kumar: between… in the team members, you have a conflict of how to approach something, right? Oh, okay.
136 00:17:38.070 ⇒ 00:17:39.469 Awaish Kumar: How would you dissolve?
137 00:17:39.750 ⇒ 00:17:41.479 Awaish Kumar: The conflict.
138 00:17:41.910 ⇒ 00:17:43.320 Johnathan Reyna: Yeah,
139 00:17:44.140 ⇒ 00:17:59.330 Johnathan Reyna: So I think, the way, like, and I’ve managed a variety of different teams that I typically resolve conflict. It’s, if it’s a one-to-one, where it’s one person against, you know, another person’s point of view, or we’re all trying to collaborate on something.
140 00:17:59.330 ⇒ 00:18:06.300 Johnathan Reyna: A lot of it is having the patience to hear people’s thoughts completely and fully before making a decision.
141 00:18:07.620 ⇒ 00:18:23.419 Johnathan Reyna: I think there’s a certain amount of trust that has to be established in any type of collaborative environment where people feel able to speak what they’re really thinking. And so in doing so, you have to have,
142 00:18:23.780 ⇒ 00:18:28.519 Johnathan Reyna: opportunities for everyone to demonstrate skill sets.
143 00:18:28.650 ⇒ 00:18:36.650 Johnathan Reyna: And then, even then, you have to build, through exercise and communication, sitting down and literally
144 00:18:36.810 ⇒ 00:18:53.200 Johnathan Reyna: I call it peeling the onion, where you’re sitting down and actually looking at what we’re really trying to solve, and if it’s, you know, two people are… have two different opposing ideas, or me as the leader doesn’t agree with what everyone else’s solution is.
145 00:18:53.360 ⇒ 00:19:02.650 Johnathan Reyna: trying to find the most amicable solution through communication is usually the approach I take. Sometimes I don’t have the ability to
146 00:19:02.870 ⇒ 00:19:20.069 Johnathan Reyna: to wait, we have to push forward, so there are times where, you know, I tell everybody, I know you guys don’t agree, but, for the sake of time, you know, this is the direction we’re gonna go, and I take ownership, stuff like that, that happens as well, so… Does that answer your question? Sorry, I missed it the first time.
147 00:19:21.030 ⇒ 00:19:33.740 Awaish Kumar: Yeah, it does. So, and apart from that, my final question is, how would you communicate your, like, your solutions, your…
148 00:19:35.970 ⇒ 00:19:41.280 Awaish Kumar: Technical, things with the non-technical stakeholders.
149 00:19:42.070 ⇒ 00:19:50.939 Johnathan Reyna: Yeah, so usually I find relative metaphors or, common, imagery that relates to technical capabilities.
150 00:19:51.140 ⇒ 00:20:10.380 Johnathan Reyna: you know, things like, I think, are great examples are for, you know, explaining something like a complicated API to an individual, you know, using the restaurant and the waiter as the example. You know, those types of ways are simplified examples to help,
151 00:20:10.700 ⇒ 00:20:12.130 Johnathan Reyna: create…
152 00:20:12.270 ⇒ 00:20:23.070 Johnathan Reyna: in general language, technical terms. I do think that there is, and you’ll find, you know, in industries or, in, in,
153 00:20:23.210 ⇒ 00:20:34.250 Johnathan Reyna: Like, even in Department of Defense or Department of War, there is certain vernacular when even trying to express something highly technical into generic language.
154 00:20:34.320 ⇒ 00:20:43.280 Johnathan Reyna: You need to know the language, you need to understand the concepts enough that you can have the translation match the correct terms.
155 00:20:43.560 ⇒ 00:20:48.200 Johnathan Reyna: But really, you know, I think visuals always, always, always help.
156 00:20:48.270 ⇒ 00:21:02.309 Johnathan Reyna: So, if I can give you something visually to consume, and you’re able to walk away with as a leader, or as a non-technical individual, you’ll have more intelligent conversations and feel like you can have, or you can…
157 00:21:02.370 ⇒ 00:21:08.509 Johnathan Reyna: you feel like you can communicate because you have a reference point, right? There’s equal language and common language being used.
158 00:21:08.600 ⇒ 00:21:13.850 Johnathan Reyna: So you can ask the questions, and I never, belittle people when they ask
159 00:21:14.700 ⇒ 00:21:17.340 Johnathan Reyna: Questions about complicated things, so…
160 00:21:18.330 ⇒ 00:21:20.970 Awaish Kumar: And how would, like, do you…
161 00:21:21.720 ⇒ 00:21:25.289 Awaish Kumar: Have an example where you had to learn a skill
162 00:21:25.550 ⇒ 00:21:28.150 Awaish Kumar: On the job, to deliver something.
163 00:21:30.430 ⇒ 00:21:36.930 Johnathan Reyna: So, just in general, or do you want, like, a technical skill, or what are you looking for there?
164 00:21:37.860 ⇒ 00:21:39.399 Awaish Kumar: Yeah, I mean, technically skilled.
165 00:21:41.430 ⇒ 00:21:55.300 Johnathan Reyna: I mean, that same… that one that I just used recently, which was, the visualization where we were doing Tableau, I’d never used Qlik before. That’s just a visualization platform, nothing crazy, still uses some…
166 00:21:55.380 ⇒ 00:22:03.099 Johnathan Reyna: baseline SQL with it, but I literally had to show up day one with no experience, and they had,
167 00:22:03.410 ⇒ 00:22:07.899 Johnathan Reyna: Historical dashboards that they needed maintained for previous usage.
168 00:22:08.080 ⇒ 00:22:12.210 Johnathan Reyna: And I had no idea how to use that, and I had to use that on the job,
169 00:22:13.060 ⇒ 00:22:18.120 Johnathan Reyna: But, you know, I found the subject matter experts, and, you know, they… they…
170 00:22:18.340 ⇒ 00:22:20.510 Johnathan Reyna: Did a good job helping me spin up quickly.
171 00:22:21.810 ⇒ 00:22:30.379 Awaish Kumar: I mean, like, you learned that tool, if you, like, how… how long it took you to onboard on that tool, and deliver…
172 00:22:30.670 ⇒ 00:22:34.940 Johnathan Reyna: Couple weeks. Couple weeks. I mean, it wasn’t a very complicated tool, it’s just…
173 00:22:35.160 ⇒ 00:22:41.630 Johnathan Reyna: figuring out where all of the… I mean, eventually, I got the client to agree to migrate away from that anyway.
174 00:22:41.870 ⇒ 00:22:45.429 Johnathan Reyna: It wasn’t as fast and robust as Tableau, so…
175 00:22:45.590 ⇒ 00:22:52.700 Johnathan Reyna: We, I think we used it for about 6 to 8 months. Took me about 6 weeks, less than 6 weeks to learn.
176 00:22:52.980 ⇒ 00:22:59.950 Johnathan Reyna: And just so that way we could establish or maintain those current… This is historic dashboards.
177 00:23:00.380 ⇒ 00:23:01.300 Awaish Kumar: Okay.
178 00:23:01.500 ⇒ 00:23:03.920 Awaish Kumar: I think that’s it from my side.
179 00:23:04.080 ⇒ 00:23:06.370 Awaish Kumar: Do you have any questions?
180 00:23:07.230 ⇒ 00:23:14.409 Johnathan Reyna: Yeah, I mean, like… working at Brainforge, what is that like for you?
181 00:23:17.180 ⇒ 00:23:20.439 Awaish Kumar: what is it like for me, being at Trading Food?
182 00:23:20.880 ⇒ 00:23:24.819 Awaish Kumar: I think it’s, it’s quite great, like,
183 00:23:25.510 ⇒ 00:23:28.359 Awaish Kumar: I have, like, it does matches my, kind of.
184 00:23:30.000 ⇒ 00:23:42.010 Awaish Kumar: like, the work style. Like, it is remote, so I can work on my schedule from whatever place I want. Secondly, it’s really fast-paced, and
185 00:23:42.450 ⇒ 00:23:48.060 Awaish Kumar: Like, you have… you get opportunity to learn like, almost…
186 00:23:48.600 ⇒ 00:23:55.310 Awaish Kumar: Like, anything, like, you can learn whatever tools you need, like, you have the… Flexibility?
187 00:23:55.600 ⇒ 00:23:58.449 Awaish Kumar: With… with a lot of accountability.
188 00:23:58.720 ⇒ 00:24:01.129 Awaish Kumar: We have new clients coming in.
189 00:24:01.540 ⇒ 00:24:17.120 Awaish Kumar: for that, you are free to choose whatever tools you think could be… could be best… best suited for that client. That comes, like, you get the flexibility to choose between the tools, but it is… it is… now, you are accountable for me, for those choices, choices, so…
190 00:24:17.760 ⇒ 00:24:20.889 Awaish Kumar: I like, being in that situation.
191 00:24:21.280 ⇒ 00:24:23.080 Awaish Kumar: I…
192 00:24:23.220 ⇒ 00:24:34.600 Awaish Kumar: have been working on my… like, I have 10 years of experience, so almost from 10 years, I’ve been working at startups. So for me, it is, like…
193 00:24:35.020 ⇒ 00:24:38.659 Awaish Kumar: Being there, sometimes it is really fast, you have to…
194 00:24:38.950 ⇒ 00:24:42.640 Awaish Kumar: Move quite a lot of things together, but yeah.
195 00:24:42.800 ⇒ 00:24:44.920 Awaish Kumar: That’s, like, that’s what I enjoy, man.
196 00:24:46.360 ⇒ 00:24:51.499 Johnathan Reyna: What would you say your typical, I mean, obviously fast-paced environments.
197 00:24:51.660 ⇒ 00:24:55.139 Johnathan Reyna: In the military, we call those op… high op tempos.
198 00:24:55.330 ⇒ 00:24:59.409 Johnathan Reyna: Where you have mission critical that needs to go out quickly.
199 00:24:59.530 ⇒ 00:25:06.429 Johnathan Reyna: and you’re not pulling a typical 9-to-5 that’s sometimes, you know, you’re pulling a 16, 14-hour day. Is that something that’s common?
200 00:25:07.200 ⇒ 00:25:09.059 Johnathan Reyna: From your experience?
201 00:25:09.990 ⇒ 00:25:13.800 Awaish Kumar: Yeah, I mean, it’s… it’s not more about,
202 00:25:13.940 ⇒ 00:25:23.609 Awaish Kumar: spending more time, it’s, like, more… taking more responsibilities, and improving… optimizing your workflows using AI.
203 00:25:23.810 ⇒ 00:25:28.870 Awaish Kumar: To deliver more than we could have delivered 5 years ago, for example.
204 00:25:28.870 ⇒ 00:25:29.580 Johnathan Reyna: Yeah, yeah.
205 00:25:29.860 ⇒ 00:25:30.820 Johnathan Reyna: That’s fair.
206 00:25:31.600 ⇒ 00:25:32.850 Johnathan Reyna: Do,
207 00:25:34.050 ⇒ 00:25:48.869 Johnathan Reyna: You know, obviously you’re saying that you’re making the decisions and accountabilities being had for the technologies for a client space. Are there requirements or partnerships that Brainforge has specifically on technologies that you try and promote?
208 00:25:49.330 ⇒ 00:25:50.590 Johnathan Reyna: Or is it just…
209 00:25:50.880 ⇒ 00:25:55.109 Awaish Kumar: Oh, it’s like, we, we don’t promote, we don’t, actually…
210 00:25:55.320 ⇒ 00:26:06.829 Awaish Kumar: just blindly use anything, just because we have a partnership. Like, we have to… we do have partners, but we don’t choose the tools blindly just because we are partners, right?
211 00:26:06.890 ⇒ 00:26:08.000 Johnathan Reyna: So we…
212 00:26:08.320 ⇒ 00:26:13.650 Awaish Kumar: choose the tools based on the client’s need. So, if a client has…
213 00:26:13.920 ⇒ 00:26:25.369 Awaish Kumar: needs, like, a tool like Snowflake, then we can… we will use that, but if there are, like, some small-scale clients where it doesn’t make sense to bring in such a
214 00:26:25.440 ⇒ 00:26:40.930 Awaish Kumar: large data platform. We work with MotherDuck, which is quite a smaller version of a modern-style data warehouse. So, there is… it depends on what kind of tools,
215 00:26:41.180 ⇒ 00:26:46.289 Awaish Kumar: We use it, and it completely depends on the use case, but yes, we do have partners.
216 00:26:46.610 ⇒ 00:26:51.620 Awaish Kumar: Which can speed things up. For example, we have a direct line with
217 00:26:52.070 ⇒ 00:26:53.929 Awaish Kumar: Quite a lot of partners, like.
218 00:26:54.520 ⇒ 00:27:06.099 Awaish Kumar: some of ETL tools and stuff like that. So, if it makes sense, we just use that, because it makes it much easier for us to, when we need, like, help, like, support.
219 00:27:06.100 ⇒ 00:27:20.879 Awaish Kumar: We just have direct Slack channels with them, we can communicate with them. Okay, this is very why… while for others, where we just have to wait through emails, like, okay, we have 48 hours of waiting period, after that, somebody will come and respond to your ticket.
220 00:27:20.900 ⇒ 00:27:21.880 Awaish Kumar: So…
221 00:27:23.090 ⇒ 00:27:32.929 Awaish Kumar: Like, it goes both ways, depends on the use cases, but also then, if some of our partners are best suited for some client, we are obviously going to use that.
222 00:27:34.150 ⇒ 00:27:38.240 Johnathan Reyna: So you said that you had 10 years’ experience in startups. What made you come to Brainforge?
223 00:27:39.380 ⇒ 00:27:40.340 Awaish Kumar: I ha-
224 00:27:41.430 ⇒ 00:27:48.469 Awaish Kumar: Yeah, so I was working… I was actually looking for a job while I was in Canada.
225 00:27:50.690 ⇒ 00:27:58.440 Awaish Kumar: And, I was working at a gaming company with… which just, basically, What’d you say?
226 00:27:58.910 ⇒ 00:28:03.420 Awaish Kumar: That was also in a startup, but they just ran out of funding.
227 00:28:04.000 ⇒ 00:28:09.750 Awaish Kumar: it got dissolved, so I was looking for jobs where I found out,
228 00:28:10.580 ⇒ 00:28:20.949 Awaish Kumar: Utam, CEO of Brainforge, in our dbt community, we connected, and I just, happened to be at Brainforge. I stayed here, and…
229 00:28:21.420 ⇒ 00:28:25.660 Awaish Kumar: for a year now, and yeah, I think it… It’s a great place.
230 00:28:27.490 ⇒ 00:28:33.040 Johnathan Reyna: Do you, what do you see Brain Forge’s, like, future look like?
231 00:28:35.010 ⇒ 00:28:42.510 Awaish Kumar: Yeah, Future is, like, it’s a consultancy service, right? That’s growing at a very fast pace.
232 00:28:43.930 ⇒ 00:28:45.629 Awaish Kumar: And, I think,
233 00:28:46.140 ⇒ 00:28:52.510 Awaish Kumar: And, like, in future it will continue to grow like that, because a lot of, like, I have worked
234 00:28:52.640 ⇒ 00:28:56.019 Awaish Kumar: Previously in the constitancy as well.
235 00:28:56.140 ⇒ 00:28:59.550 Awaish Kumar: Where it was more, like, a lot of politics, a lot of,
236 00:28:59.870 ⇒ 00:29:07.300 Awaish Kumar: Like, legacy workflows, processes, where you deal with those, and then,
237 00:29:09.630 ⇒ 00:29:13.220 Awaish Kumar: Whereas at Windforce, it’s completely new.
238 00:29:13.610 ⇒ 00:29:24.489 Awaish Kumar: company, like, quite young company with a lot of new processes, like, everybody, is AI-enabled here, like, even from
239 00:29:25.060 ⇒ 00:29:36.719 Awaish Kumar: sales, marketing, everybody, like, technical or non-technical, everybody uses AI to improve their workflows, so we don’t have any rigid legacy processes here.
240 00:29:37.000 ⇒ 00:29:50.369 Awaish Kumar: And a lot of, like, very less friction on how… when to onboard client, when to deliver value, so we don’t look for, like… when a client comes, we don’t wait for, like, 6 months to actually tell them, we have delivered something here.
241 00:29:50.530 ⇒ 00:29:55.319 Awaish Kumar: Like, in 6 weeks of time, we show to the client that we have
242 00:29:55.440 ⇒ 00:29:59.369 Awaish Kumar: meaningful deliverables for you. And so they stay with us.
243 00:29:59.970 ⇒ 00:30:00.780 Awaish Kumar: So…
244 00:30:01.100 ⇒ 00:30:01.530 Johnathan Reyna: Our most.
245 00:30:01.870 ⇒ 00:30:02.620 Awaish Kumar: Saved.
246 00:30:03.000 ⇒ 00:30:06.190 Johnathan Reyna: How are most technical teams developed at Brainforge?
247 00:30:07.600 ⇒ 00:30:11.389 Awaish Kumar: And…
248 00:30:12.140 ⇒ 00:30:17.120 Johnathan Reyna: development teams, do you guys have development teams, or is it just… How are you guys structured?
249 00:30:17.450 ⇒ 00:30:24.079 Awaish Kumar: yeah, normally, no, most of our clients are, like,
250 00:30:24.720 ⇒ 00:30:30.940 Awaish Kumar: We are structured in a pods, like… like… Where we have, like.
251 00:30:31.200 ⇒ 00:30:38.290 Awaish Kumar: people, from specialized skills to become part of that board. For example, if we have an
252 00:30:38.530 ⇒ 00:30:41.449 Awaish Kumar: Client, which needs their engineering skills.
253 00:30:41.570 ⇒ 00:30:48.919 Awaish Kumar: when we have one data engineer, one PM, which will manage tickets, or maybe, and then we will have one more person there.
254 00:30:48.960 ⇒ 00:31:03.459 Awaish Kumar: For, for example, a data analysts or something, and we continue work in that port. For example, if that client grows their scope from just requiring data engineering service to maybe requiring more product analytics kind of services.
255 00:31:03.520 ⇒ 00:31:10.950 Awaish Kumar: Then we’ll have a few more people joining in into that port. But, like, those… these ports operate independently.
256 00:31:11.510 ⇒ 00:31:15.129 Awaish Kumar: Like, product engineering,
257 00:31:15.340 ⇒ 00:31:22.830 Awaish Kumar: Although we are part of the same client, we… we can work… we can plan our… projects,
258 00:31:23.420 ⇒ 00:31:24.880 Awaish Kumar: According to what…
259 00:31:25.340 ⇒ 00:31:39.310 Awaish Kumar: Whatever availability we have, like, for example, product analytics engineer can spend 20 hours on doing product analytics, and wherever they need help from data engineer, they just will create some tickets there.
260 00:31:39.470 ⇒ 00:31:46.819 Awaish Kumar: And then we are going to work in the sprints to bring in, okay, what is needed. So it’s, kind of the same structure. Normally.
261 00:31:47.210 ⇒ 00:31:51.210 Awaish Kumar: For every client, we have Two to three people assigned.
262 00:31:51.640 ⇒ 00:32:00.070 Awaish Kumar: And, and… and that’s how we operate, like, that’s kind of our structure of oper…
263 00:32:01.770 ⇒ 00:32:04.610 Awaish Kumar: Like, operating, on, on the client work.
264 00:32:05.170 ⇒ 00:32:11.059 Awaish Kumar: And that… how that pork grows completely depends on kind, requirements, like…
265 00:32:11.160 ⇒ 00:32:15.329 Awaish Kumar: How much, like, they want to grow their scope, right?
266 00:32:16.270 ⇒ 00:32:16.780 Johnathan Reyna: Nope.
267 00:32:16.940 ⇒ 00:32:19.830 Johnathan Reyna: Did, and I know we’re almost at time… do,
268 00:32:20.250 ⇒ 00:32:26.700 Johnathan Reyna: You said tickets, obviously, so are you guys using, Jira, or are you guys using Confluence, or…
269 00:32:27.380 ⇒ 00:32:28.539 Awaish Kumar: We use linear.
270 00:32:28.790 ⇒ 00:32:29.410 Johnathan Reyna: Okay.
271 00:32:29.600 ⇒ 00:32:32.260 Awaish Kumar: similar to Jira, some of the.
272 00:32:32.260 ⇒ 00:32:36.370 Johnathan Reyna: They all are similar. They’re usually all similar, just very…
273 00:32:36.890 ⇒ 00:32:37.580 Awaish Kumar: Right.
274 00:32:39.250 ⇒ 00:32:40.030 Johnathan Reyna: Okay.
275 00:32:40.370 ⇒ 00:32:49.389 Awaish Kumar: Yeah. Okay, I think, we are at the end of the time, so it was… thank you for taking, taking the time for the interview, and…
276 00:32:49.640 ⇒ 00:32:55.149 Awaish Kumar: Rico from Over Operations team will come back to you, maybe in a week’s time, with the next steps.
277 00:32:55.580 ⇒ 00:32:57.300 Awaish Kumar: Yeah, thank you.
278 00:32:57.690 ⇒ 00:32:58.549 Johnathan Reyna: Awesome, thanks.