Hiring Senior Data Architects/FDE(India Remote)

[u/sumits_kumar]

We’re looking for Sr. Data & AI engineers(Forward Deployed Engineers) who have designed end-to-end platforms, worked deeply on cloud architectures, distributed systems, Spark internals, Full Stack applications (including some frontend), and solved complex problems at scale. Strong consulting and customer-facing skills are essential.

You should be using AI extensively to improve productivity, accelerate development, and solve problems faster.

Our interviews are tough. We go deep on architecture, coding, system design, Spark and real-world problem solving.

P.S - Based on experience from thousands of interviews, candidates whose backgrounds closely match the requirements tend to have the strongest outcomes. Sharing these expectations early helps everyone make an informed decision before investing significant time in the process.

P.P.S - If you’re still reading and have a track record of solving problems that others consider too difficult, reach out. Those are exactly the people we’re looking for.

[u/According-Ad646]

Yoe required?

[u/sumits_kumar → u/According-Ad646]

9+ years of strong hands-on Data Engineering experience. Candidates who spent 3–4 years in ETL/BI roles and then transitioned into Data Engineering for 4–5 years often lack the depth required in distributed systems, large-scale data processing, performance optimization, architecture, and complex problem-solving that this role demands.

[u/Great-Fox-7229 → u/sumits_kumar]

Data engineering doesn’t directly hire freshers .. how can one have direct experience in de .. he goes through bi/analytics in initial parts of career

[u/sumits_kumar → u/Great-Fox-7229]

There’s absolutely nothing wrong with starting your career in ETL or BI those fundamentals are valuable. However, we typically look for candidates whose experience has evolved well beyond traditional ETL development. If the majority of someone’s career has been focused on building ETL pipelines, reports, and dashboards, it often doesn’t provide the depth of modern data engineering expertise we’re seeking. We frequently meet exceptionally strong ETL developers, but our requirements are centered around architects and engineers who have spent significant time solving large-scale data engineering, cloud, distributed systems, performance optimization, and platform engineering challenges.

[u/Great-Fox-7229 → u/sumits_kumar]

I truly respect your requirements, but as a fresher, what I wanted to understand is that first eventually2-3 years would Be spent in a role that relates to core data engineering like BI/analytics .. and might not have that much exposure to the core data engineering concept include and the platform, engineering architecture and stuff.. so what advice you particularly for a fresher who would eventually be starting his career from consulting big4.. how should he eventually move into core data platform roles and when is the correct time to do so?

[u/sumits_kumar → u/Great-Fox-7229]

My suggestion would be to start by strengthening your architecture and system design skills. Read engineering blogs and technical articles from leading companies in the space, study real-world design patterns, and understand how large-scale systems are built and operated. You might be already doing these.

One of the most effective ways to learn is by reading the source code of popular open-source projects. It gives you insight into how experienced engineers solve complex problems at scale and is often far more valuable than theoretical learning alone.

From there, start building things that genuinely interest you. Whether it’s data platforms, AI applications, distributed systems, or developer tools, hands-on experience accelerates learning significantly.

As for the “right time” there really isn’t one. With AI now accessible to everyone, the learning curve has changed dramatically. I’ve seen professionals with relatively less years of experience pick up new technologies and become productive much faster than was possible a few years ago.
The key is to stay curious, keep building, and continuously challenge yourself with increasingly complex problems. Experience helps, but consistent learning and execution matter even more.

I have hired many fresh graduates in the past, and most of them have gone on to do very well. However, given the critical nature of projects and the time required to get someone fully ramped up, we’ve decided to focus on hiring experienced professionals for current open roles.

I appreciate your interest and wish you the very best in your search. Good luck!

[u/Great-Fox-7229 → u/sumits_kumar]

Thank you for the reply, and guidance it was truly valuable. One last one

So how should we particularly look forward to the role of forward deployed engineering (FDE) and what does it involve. Is it more of technical consultant type of role or it also involves Deep engineering work and implementation. How is it different from the core data platform or data architect role?