EPAM Data Analyst candidates report an HR conversation, a hands-on technical interview in SQL, Python and Power BI, and in one case a project manager discussion. Here is what to practice and what to expect.
$100K
Avg. Base Comp
$130K
Avg. Total Comp
Not reported
Typical Rounds
3-4 weeks
Process Length
Candidates describing EPAM Data Analyst interviews most often point to SQL, Python and Power BI/DAX as the core of the technical conversation. One 1.5-hour technical interview opened with a review of the candidate's experience, then moved to live SQL with four questions covering aggregation, window functions and joins. The interviewer reportedly cared more about logic and syntax knowledge than fully working code. Python questions were described as easy and covered DataFrames and writing a function. The Power BI portion asked about DAX and calculated columns, and the candidate was shown a dashboard and asked what they would change to make it more readable.
Another candidate described a similar mix: Python lambda functions and list comprehensions, SQL window functions, UNION versus UNION ALL, and NVL, followed by scenario-based analysis questions and a discussion with a project manager about soft skills and team fit. A third reported multiple rounds over nearly a month, with SQL, Power BI, DAX and practical reporting scenarios alongside managerial and project discussions.
Communication is the other recurring theme. Candidates mention rescheduling, conflicting status updates and silence after the technical stage. Several reports ended without an offer, so prepare to explain your reasoning aloud and expect the timeline to stretch. Senior-level reports are mixed in here: one asked about materialized versus regular views, and another centered on a medium SQL window-function exercise.
Synthesized from 5 candidate reports by our editorial team.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report the process typically begins with an HR or recruiter contact, sometimes through LinkedIn. One candidate described this screen as focused on background, experience and standard behavioral questions. Be ready to summarize your analytics projects and the tools you have used, especially SQL and Power BI.
This stage appears in the reports as a hands-on technical interview. One lasted about 1.5 hours and included four SQL questions on aggregations, window functions and joins, plus easy Python DataFrame and function questions. Another candidate reported lambda functions, list comprehensions, UNION versus UNION ALL and NVL. Interviewers may care more about your logic than perfectly working code.
Candidates report Power BI and DAX questions, including calculated columns. One was shown a dashboard and asked what they would change to make it more readable. Practice explaining how you would turn an analysis into a clear report, and how you would apply DAX to realistic reporting scenarios.
Candidates describe situational or scenario-based questions, and one reports a discussion with a project manager covering soft skills, cultural fit and how they would work within the team. Another mentions managerial and project conversations. Prepare examples of past projects, and note that follow-up may be slow or inconsistent, with some candidates reporting conflicting status updates or no reply.
