Exl Data Engineer interviews reported by candidates combine SQL and warehousing questions, Spark and pipeline design discussion, and a managerial or HR conversation. Reports describe about 3-4 rounds.
$113K
Avg. Base Comp
$140K
Avg. Total Comp
3-4 rounds
Typical Rounds
Not reported
Process Length
Candidates describe Exl Data Engineer interviews as a mix of hands-on SQL, data warehouse knowledge and architecture discussion, followed by a managerial or HR conversation. Four reports are available, and they differ in detail, so treat the rounds below as examples rather than a fixed script.
SQL is the most consistent theme. One candidate was asked medium-level problems using LEAD and LAG, such as finding stores whose monthly sales beat the prior month at least once. Another was asked to work out row counts from different join types, including how nulls behave. A third reported five or six queries covering unions and window functions. Practise window functions and join cardinality until you can reason through them out loud.
Beyond SQL, the technical rounds moved toward design. One candidate had a hands-on round in Python, Spark and SQL, then a round on data warehouse design and AWS. Another was asked to explain incremental ingestion and design an end-to-end pipeline, with follow-ups on scalability, fault tolerance and monitoring. A third reported Azure concepts such as triggers and integration runtimes, plus PySpark, orchestration and batch versus streaming trade-offs. Be ready to explain why you would choose an approach, not only how.
The later rounds were softer. One candidate described a managerial round on accountability, ownership and awareness of new technology. Another had a face-to-face client round. HR rounds covered project walkthroughs, salary expectations and fit. Outcomes were mixed: one offer, one offer that was declined, and two rejections. One of the rejections followed a reported hold on the position.
Synthesized from 4 candidate reports by our editorial team.
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| Question | |
|---|---|
| Employee Salaries | |
| Size of Joins | |
| Hurdles In Data Projects | |
| Target Indices | |
| Transformer Encoder Layer | |
| P-value to a Layman | |
| Duplicate Rows | |
| RAG Strict Source Control | |
| Type I and II Errors | |
| Swap Variables | |
| Data Preparation for Imbalanced Data | |
| Assumptions of Linear Regression | |
| Multicollinearity in Regression | |
| Your Strengths and Weaknesses | |
| Google Earth Storage | |
| Branch Sales Pivot | |
| Linear vs Logistic Regression | |
| Correlation in Regression | |
| Designing a Fraud Detection System | |
| Random SQL Sample | |
| Random Forest Explanation | |
| Cyclic Detection | |
| WAU vs Open Rates | |
| Classification and Regression | |
| Modifying a Billion Rows | |
| Same Characters | |
| Integer String Addition | |
| Success Measurement | |
| Possibly Biased Coin |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial screen before the technical rounds. One described a roughly 30-minute recruiter call, and another a resume screening. Expect a short conversation about your background and role fit, though the exact content may vary.
Candidates report a first technical round centered on SQL and data warehousing. Reported questions include LEAD/LAG sales comparisons, join row counts, window functions and unions. One candidate also had hands-on Python and Spark coding plus project questions, and another was asked about incremental ingestion.
Some candidates describe a second technical round that is more about design than coding. Reported topics include data warehouse design, AWS or Azure concepts, PySpark, orchestration, batch versus streaming, and end-to-end pipeline design with scalability, fault tolerance and monitoring follow-ups.
Reports include a managerial round covering accountability, leadership, owning a task and awareness of new technology. One candidate described scenario questions about approaching project problems. Another reported a face-to-face client round as the final stage. Not every candidate described this round.
Candidates report an HR conversation that may cover self-introduction, project walkthroughs, salary expectations, cultural fit and offer details. One candidate received offer details at this stage. Another was told the position was on hold.
