Meeting Title: Brainforge x Sebastien Henry Interview Date: 2026-03-24 Meeting participants: Sebastien Henry, Kaela Gallagher
WEBVTT
1 00:00:56.110 ⇒ 00:00:57.899 Kaela Gallagher: Hi, how’s it going?
2 00:00:57.900 ⇒ 00:01:00.629 Sebastien Henry: Hello, good afternoon! Good evening!
3 00:01:00.890 ⇒ 00:01:01.960 Kaela Gallagher: Una.
4 00:01:02.150 ⇒ 00:01:09.900 Kaela Gallagher: I am doing well, thanks for taking the time to meet with me. Appreciate it, so glad that, Chad was able to connect us.
5 00:01:10.540 ⇒ 00:01:12.059 Sebastien Henry: Yeah, and likewise.
6 00:01:12.310 ⇒ 00:01:30.099 Kaela Gallagher: Awesome. Yeah, I guess just starting off, would love to learn, like, a little bit more about your background, and then I can tell you more about what we’re… we’re doing at Brainforge. But I think Chad mentioned that you might be looking for something new, so curious what is putting you on the market.
7 00:01:31.320 ⇒ 00:01:40.100 Sebastien Henry: Well, yes, he’s right. I’m looking for new opportunities, because it will be almost 8 years of work for Indeed.
8 00:01:40.290 ⇒ 00:01:42.500 Sebastien Henry: And,
9 00:01:42.740 ⇒ 00:01:51.399 Sebastien Henry: I think I do everything I can about around Tableau and Salesforce, and I’m looking for opportunities around AI.
10 00:01:51.680 ⇒ 00:01:58.000 Sebastien Henry: Data engineering or, solution architect with a cloud application.
11 00:01:58.940 ⇒ 00:02:01.910 Kaela Gallagher: Okay, and you’re still with Indeed, you said?
12 00:02:02.170 ⇒ 00:02:03.679 Sebastien Henry: That’s correct.
13 00:02:03.900 ⇒ 00:02:06.529 Kaela Gallagher: Okay, and you’re based in Austin, right?
14 00:02:06.800 ⇒ 00:02:07.760 Sebastien Henry: That’s correct.
15 00:02:07.760 ⇒ 00:02:17.190 Kaela Gallagher: Okay, cool. Our, CEO is actually based in Austin, so, that’s like a huge bonus for us that you’re there. Maybe you guys could meet.
16 00:02:17.300 ⇒ 00:02:27.830 Kaela Gallagher: Okay, cool. Can you tell me, like, more about the work that you’ve been doing at Indeed? I noticed that you started more on, like, the BI kind of development side, and now you’ve come over to, like.
17 00:02:27.830 ⇒ 00:02:28.220 Sebastien Henry: God.
18 00:02:28.220 ⇒ 00:02:29.450 Kaela Gallagher: engineering? Okay.
19 00:02:29.450 ⇒ 00:02:48.330 Sebastien Henry: Well, my, my, my journey at EE was kind of at, I would say, special, because I started as BI, analyst, and, as a very first time, my first, my first boss, run shipments.
20 00:02:48.370 ⇒ 00:03:03.929 Sebastien Henry: see, I have a lot of potential with Tableau, and they bring with me into Tableau Product, where we create a community, we help people to design anything with Tableau, but also, migrate to,
21 00:03:04.480 ⇒ 00:03:07.350 Sebastien Henry: Innovation Lead?
22 00:03:07.520 ⇒ 00:03:19.810 Sebastien Henry: through, through Chad, where I created some solution out of box. In other, it can be very useful for the Tableau community we build. Actually, we have,
23 00:03:19.960 ⇒ 00:03:28.190 Sebastien Henry: I would say, 5,000 people use the Tableau.
24 00:03:28.570 ⇒ 00:03:29.060 Sebastien Henry: And…
25 00:03:29.610 ⇒ 00:03:42.049 Sebastien Henry: actively, but we have some basic users. So, what I do, for example, I create some connectors in order to connect our main solution of big data.
26 00:03:42.160 ⇒ 00:03:46.759 Sebastien Henry: And in others, you can get data and put… create some dashboards in Tableau.
27 00:03:47.020 ⇒ 00:03:58.649 Sebastien Henry: create several crunch jobs, do some data creation, but also push to get, side services like PapPi in order we can do machine learning inside Tableau.
28 00:03:59.440 ⇒ 00:04:02.089 Sebastien Henry: After, reorg.
29 00:04:02.260 ⇒ 00:04:12.199 Sebastien Henry: I come back to BI, where I design some dashboard and start to do something with EI, not with Tableau, but with Snowflake Cortex.
30 00:04:12.490 ⇒ 00:04:21.359 Sebastien Henry: create my… I have to create the first chatbot in Slack and connect it to Cortex for invoice data.
31 00:04:21.630 ⇒ 00:04:23.569 Sebastien Henry: And another reorg?
32 00:04:23.790 ⇒ 00:04:29.590 Sebastien Henry: And, now, I am project manager of Tableau Next.
33 00:04:29.960 ⇒ 00:04:34.369 Sebastien Henry: We’re required to promote Immersion, this project.
34 00:04:34.510 ⇒ 00:04:38.490 Sebastien Henry: It’s not perfect, but,
35 00:04:38.620 ⇒ 00:04:45.330 Sebastien Henry: I have some hope, you know, that we can make more projects with that, especially with sales and marketing.
36 00:04:46.120 ⇒ 00:04:53.419 Kaela Gallagher: Okay, okay, very cool. I think that experience could be really relevant to, kind of, what we’re doing.
37 00:04:53.690 ⇒ 00:05:01.529 Kaela Gallagher: Right now, we’re hiring for an analytics engineer position, as well as, like, a data engineer role.
38 00:05:01.530 ⇒ 00:05:13.799 Kaela Gallagher: and then an AI and automation engineer role. Based on what you’ve told me, I would guess that your background kind of fits our analytics engineer role the best. Curious if that sounds right to you as well.
39 00:05:14.640 ⇒ 00:05:25.079 Sebastien Henry: Well, analytics is my main things, but, in mid-long term, I would like to do more and more EI, projects. I don’t have so much…
40 00:05:25.480 ⇒ 00:05:48.670 Sebastien Henry: opportunity that, indeed, to have some EI projects. That’s why you see on my resume, I don’t have so much, but you can see I have some proj… I create some projects on my side, because I’m learning always on my side. I do some Udacity, and I will, I will get… I hope I will get my master on EI this Friday.
41 00:05:49.290 ⇒ 00:06:04.009 Sebastien Henry: Yeah, I’d like to present something, but we will see. And, again, some experience with EI, and you probably have a link on my GitHub where I have several EI projects.
42 00:06:04.770 ⇒ 00:06:05.380 Sebastien Henry: But, yeah.
43 00:06:05.380 ⇒ 00:06:05.860 Kaela Gallagher: Bye!
44 00:06:05.860 ⇒ 00:06:10.660 Sebastien Henry: Either long term, I would like to do that, but also, I have some experience of data engineering, and .
45 00:06:11.790 ⇒ 00:06:26.780 Kaela Gallagher: Okay, okay, cool. Yeah, we are a 25-person company right now, so definitely a lot of room, like, even if we do have you kind of interview for this analytics engineer position and come into that role, there’s a lot of room to
46 00:06:26.780 ⇒ 00:06:33.479 Kaela Gallagher: take on other… other projects, and work with our AI team, and maybe even transition there as well.
47 00:06:33.480 ⇒ 00:06:39.690 Kaela Gallagher: We actually have somebody that’s, like, an AI engineer right now who’s really interested in sales.
48 00:06:39.690 ⇒ 00:06:56.710 Kaela Gallagher: So he’s, like, taking on sales calls and, like, meeting with clients, and so it’s really cool. I feel like if you express interest in, you know, learning something new or, working on other projects, like, that’s, you know, a culture that we, like, really support.
49 00:06:57.000 ⇒ 00:07:09.639 Kaela Gallagher: Currently, we’re also fully remote as an organization. We’re mostly working maybe, like, Central Time U.S. or Eastern Time U.S, and we have some, like, talent overseas.
50 00:07:09.650 ⇒ 00:07:28.279 Kaela Gallagher: So definitely, like, a global organization, and our teams are, for the most part, split into, like, three kind of service lines. So one is data, which this analytics engineering role falls under, one is AI, and one is, strategy and analytics.
51 00:07:28.410 ⇒ 00:07:35.210 Kaela Gallagher: So these teams are able to support our clients in different ways, but oftentimes there’s, you know, a lot of overlap.
52 00:07:35.350 ⇒ 00:07:43.780 Kaela Gallagher: And yeah, we’re structuring our positions right now on a 1099, contracting basis.
53 00:07:43.900 ⇒ 00:07:53.590 Kaela Gallagher: Although, you know, we hope to be able to convert people to W-2 in the future, just want to give you a heads up that the role would be structured as 1099 to start.
54 00:07:55.480 ⇒ 00:07:56.140 Sebastien Henry: Okay.
55 00:07:56.550 ⇒ 00:08:01.730 Kaela Gallagher: Any questions about any of that, or Brain Forge in general?
56 00:08:02.020 ⇒ 00:08:09.109 Sebastien Henry: I’m sorry, I’m not very familiar about your company, so…
57 00:08:09.310 ⇒ 00:08:09.740 Kaela Gallagher: Yeah.
58 00:08:09.740 ⇒ 00:08:12.950 Sebastien Henry: What kind of services you provide, what kind of…
59 00:08:13.220 ⇒ 00:08:15.579 Sebastien Henry: Your product is possible to present.
60 00:08:15.880 ⇒ 00:08:30.490 Kaela Gallagher: So, we are a data and AI consulting firm, so, data and AI services that kind of fall under those three pillars that I mentioned. Most of our clients are, like, small to mid-sized organizations,
61 00:08:30.490 ⇒ 00:08:41.850 Kaela Gallagher: But we do, like, for example, work with, like, consumer goods brands that are, like, sold in Target and Walmart. So, like, some pretty, like, well-known organizations.
62 00:08:41.850 ⇒ 00:08:50.660 Kaela Gallagher: We also work with, like, a healthcare company, or, like, a financial company, software as a service, so across different industries.
63 00:08:50.960 ⇒ 00:08:58.450 Kaela Gallagher: A lot of our engagements are short-term, maybe 3 to 6 months, where we have a very defined scope that we’re going in to kind of solve.
64 00:08:58.510 ⇒ 00:09:14.980 Kaela Gallagher: But for other clients, like, we’ve worked with them for, you know, over a year, and we serve as more of, like, an in-house, data team to them, almost. So, kind of depends on the clients, but you would probably be serving, like, two to three clients at a time.
65 00:09:15.910 ⇒ 00:09:17.649 Sebastien Henry: Okay, good, and
66 00:09:18.030 ⇒ 00:09:29.610 Sebastien Henry: What kind of technology… technology you use, is it the same kind of tools, that Chad, he sent me the project, is the same kind of tools you use?
67 00:09:30.430 ⇒ 00:09:38.910 Kaela Gallagher: Yeah, so internally, we’re using, like, Cursor, as our main, like, tool, I guess.
68 00:09:38.910 ⇒ 00:09:40.340 Sebastien Henry: I do too.
69 00:09:40.340 ⇒ 00:09:56.399 Kaela Gallagher: Okay, perfect. With our clients, we are able to kind of adapt if they already have something in place that we need to work with, but we do use Snowflake quite a bit, and then we use a BI tool called Omni quite a bit as well. I’m not sure if you’ve heard of it, but…
70 00:09:56.610 ⇒ 00:10:00.379 Kaela Gallagher: Okay, yeah, kind of similar to, like, Tableau, so…
71 00:10:00.560 ⇒ 00:10:01.190 Sebastien Henry: Okay.
72 00:10:01.190 ⇒ 00:10:09.420 Kaela Gallagher: Yeah one more question for you, I’m curious the compensation range that you’re targeting.
73 00:10:10.200 ⇒ 00:10:17.560 Sebastien Henry: To be honest with you, actually, my current salary is $175, plus all the advantage affiliate, and
74 00:10:17.670 ⇒ 00:10:25.690 Sebastien Henry: I can seriously think to make a move, like, for a minimum, 225.
75 00:10:26.330 ⇒ 00:10:38.749 Kaela Gallagher: Okay, okay, got it. I think that that is, like, something that we could meet definitely, like, at the top of our, range, but I do think your experience is really relevant, and it’s, like, worth moving forward.
76 00:10:38.850 ⇒ 00:10:55.980 Kaela Gallagher: And having you speak with our… our team. What our interview process looks like is we have kind of an initial round with one of our engineers. He’s, like, our, kind of primary data engineer person. He’ll just kind of talk about your experience in general.
77 00:10:55.980 ⇒ 00:11:14.689 Kaela Gallagher: And then our second round is a little bit more technical. No, like, live coding or anything like that, but just, like, diving in a little bit deeper to things that you’ve created. That’s with, like, our head of analytics engineering, and then our final round is a panel. We’ll send you, like, a take-home kind of challenge to solve.
78 00:11:14.690 ⇒ 00:11:17.979 Kaela Gallagher: And then have you bring your solution to the final panel.
79 00:11:18.810 ⇒ 00:11:21.450 Sebastien Henry: the same kind that Chad would get, right?
80 00:11:22.000 ⇒ 00:11:23.120 Kaela Gallagher: The same what?
81 00:11:23.120 ⇒ 00:11:27.530 Sebastien Henry: The same kind of project that the chat, get in the past, correct?
82 00:11:28.380 ⇒ 00:11:32.420 Kaela Gallagher: Yes, I think you’ve already solved it. Did I hear that?
83 00:11:32.420 ⇒ 00:11:45.149 Sebastien Henry: Yeah, but to be very honest with you, I use CureSource, I just do the prompting, and he builds for me, you have some back and forth, but yeah, the things work, so…
84 00:11:45.540 ⇒ 00:11:51.080 Kaela Gallagher: Okay, okay, cool, so yeah, you already have a sneak peek of what that’ll look like.
85 00:11:51.240 ⇒ 00:11:52.270 Kaela Gallagher: Cool.
86 00:11:52.410 ⇒ 00:11:57.510 Kaela Gallagher: Awesome! Like, any other questions for me? Anything I can help.
87 00:11:57.510 ⇒ 00:12:00.609 Sebastien Henry: This…
88 00:12:00.750 ⇒ 00:12:18.380 Sebastien Henry: If I decide to work with you, you… well, we have to be honest, maybe I have some, some… some place I have to… to learn. You provide also training inside the… your company?
89 00:12:18.760 ⇒ 00:12:30.640 Kaela Gallagher: Yes, so that I… that’s kind of what I was brought in to help bring structure to. I’m, like, leading all of our people in recruiting efforts, so that includes, you know, learning and development.
90 00:12:30.640 ⇒ 00:12:43.249 Kaela Gallagher: We do have a program to not only pay you for the time it takes to do, you know, like, training or a certification, but then also, like, pay you a bonus once the certification is completed.
91 00:12:43.310 ⇒ 00:12:50.670 Kaela Gallagher: So yeah, we definitely want to, like, encourage a culture of continuous learning and growth, for sure.
92 00:12:51.070 ⇒ 00:12:51.790 Sebastien Henry: Okay.
93 00:12:52.200 ⇒ 00:12:54.390 Sebastien Henry: Of our specification, is that…
94 00:12:54.620 ⇒ 00:13:08.449 Sebastien Henry: is that decided by the… the managers, or it’s something you can be open, like, hey, I see this certification, maybe I… it can be a good fit for us if I can do this, or I can do that.
95 00:13:08.450 ⇒ 00:13:27.760 Kaela Gallagher: Yes, we’re super open to you suggesting certifications. Right now, our CEO, like, did ask our strategy team to do, like, an Omni certification, since that’s a tool that we’re implementing with a lot of our clients. So, it might be like that, where we notice a need on our team, and we ask you to do it.
96 00:13:27.760 ⇒ 00:13:38.480 Kaela Gallagher: But we’ve also had team members, you know, ask to do, like, a DBT certification, and that’s been approved. As long as it’s, like, approved ahead of time, it’s totally fine.
97 00:13:38.500 ⇒ 00:13:39.290 Kaela Gallagher: Yeah.
98 00:13:40.430 ⇒ 00:13:48.670 Sebastien Henry: Yeah, because, for my personal growth, like I say, I hope I will have the master’s on AI after that.
99 00:13:49.070 ⇒ 00:13:53.379 Sebastien Henry: We’ll probably switch on, Databricks or Snowflake.
100 00:13:53.740 ⇒ 00:13:55.240 Sebastien Henry: certification, so…
101 00:13:55.240 ⇒ 00:13:56.030 Kaela Gallagher: Perfect.
102 00:13:56.740 ⇒ 00:14:02.690 Sebastien Henry: So if it can be… if we work together, it can be, useful for both, it would be great.
103 00:14:03.030 ⇒ 00:14:03.380 Kaela Gallagher: Yeah.
104 00:14:03.380 ⇒ 00:14:04.000 Sebastien Henry: Appreciate it.
105 00:14:04.450 ⇒ 00:14:19.649 Kaela Gallagher: Yeah, okay, awesome. Well, I’ll go ahead and send you, like, an email follow-up with a link to schedule the first round, and then just let me know if you have any questions during the process at all. I’m here, I’m here to help.
106 00:14:19.880 ⇒ 00:14:20.870 Sebastien Henry: Sure, sounds good.
107 00:14:20.870 ⇒ 00:14:22.839 Kaela Gallagher: Okay, okay, awesome.
108 00:14:22.840 ⇒ 00:14:23.330 Sebastien Henry: measure.
109 00:14:23.330 ⇒ 00:14:25.230 Kaela Gallagher: Thanks for your time. Great meeting you.
110 00:14:25.230 ⇒ 00:14:25.909 Sebastien Henry: Have a good one!
111 00:14:25.910 ⇒ 00:14:27.859 Kaela Gallagher: Alrighty. You too. Bye.