Genpact data engineer candidates describe database fundamentals, practical ETL and pipeline questions, and a same-day technical and managerial interview. Reports are few and outcomes are mixed.
$75K
Avg. Base Comp
$100K
Avg. Total Comp
3 rounds
Typical Rounds
1 week
Process Length
Reports on Genpact data engineer interviews are limited, so read them as a few candidates' experiences rather than a fixed loop.
One data engineer described a three-round process over about a week, a timeline that comes from a single report. The first round covered database fundamentals: joins, stored procedures and indexing. The second moved to practical data engineering: why ETL matters, handling large-scale processing, past tools, data modeling, schema design, data quality in pipelines and cloud platforms, plus a behavioral question about a challenging data problem. That candidate received no offer after being given negative feedback that conflicted with what the panel had said about their performance.
A different candidate had a same-day interview that began with a technical round of about an hour and fifteen minutes on SQL, PySpark and Databricks. Questions included ACID properties, differences between data lake storage services, intermediate SQL queries and basic PySpark operations. A managerial round followed. This candidate felt the manager wanted preset answers repeated back, received an offer the same day and declined it.
A principal consultant data engineer with seven years of experience also described an interviewer who seemed unprepared and looked for one correct answer, and did not receive an offer.
The technical content looks fair and practical. Practice SQL joins, PySpark basics and ETL design, and be ready to explain your reasoning clearly, since two candidates found the interviewer's approach rigid.
Synthesized from 5 candidate reports by our editorial team.
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Real interview reports from people who went through the Genpact process.
I got the offer, but I declined it. Here's what happened.
Same-day interview process. The technical round ran about an hour and fifteen minutes covering SQL, PySpark, and Databricks—and honestly, it went really well. They asked about ACID properties, differences between data lake storage services, intermediate SQL queries, and basic PySpark operations. All fair questions, and I felt confident with my answers walking out of there.
Then the managerial round started. That's where it all fell apart. The manager came in with very specific answers already locked in and basically wanted me to just echo them back. He wasn't actually interested in listening to how I think through problems—he was just waiting for me to say whatever he expected to hear. His whole attitude during that interview was rigid and dismissive, and I really didn't like it.
I got the offer by end of day, but declining was an easy call after that experience. The technical interview was solid and well-run, but the managerial round told me everything I needed to know about what working there would be like. Not worth compromising on that.
Prep tip from this candidate
The managerial round can be a deal-breaker even if the technical portion goes smoothly. Watch for whether your interviewer is genuinely curious about your thinking or just wants you to parrot back preset answers—that's a strong signal about the actual work environment.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Genpact
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Synthesized from candidate reports. Individual experiences may vary.
One data engineer, in a three-round process that took about a week, reports that the first round covered foundational database concepts: joins, stored procedures and indexing. The candidate felt it went reasonably well. Brush up on these basics and be ready to explain them plainly.
The same candidate says the second round turned practical. Questions covered the ETL process and why it matters, large-scale data processing, tools used before, data modeling and schema design, and how to ensure data quality in pipelines. Behavioral questions asked about a challenging data problem and cloud platform experience. The candidate got no offer after negative panel feedback.
A different data engineer describes a technical round of about an hour and fifteen minutes covering SQL, PySpark and Databricks. Questions included ACID properties, differences between data lake storage services, intermediate SQL queries and basic PySpark operations. The candidate felt confident leaving the room.
In that same-day process, a managerial round followed the technical one. The candidate felt the manager wanted preset answers repeated back and was not interested in how they reason. They received an offer by end of day and declined. A principal consultant data engineer separately described an unprepared interviewer looking for one correct answer and received no offer.
