EY Data Analyst interview typically runs 3 rounds: HR screening, technical interview, and manager/director interview. It usually takes about a month and is fairly conversational, with role-specific depth.
$70K
Avg. Base Comp
$120K
Avg. Total Comp
3-4
Typical Rounds
3-5 weeks
Process Length
We’ve seen EY interviewers spend a lot of time testing whether candidates can explain real work clearly, not just recite tool names. In the strongest experience, the conversation stayed relaxed but still went deep on Power BI and Power Query, with follow-ups on the candidate’s own project, data sources, transformations, and design choices. That pattern shows up elsewhere too: even when the technical content was lighter, interviewers kept returning to what the candidate had actually delivered, how they handled hurdles, and whether they could defend decisions from prior projects. EY seems to care less about polished theory and more about whether you can walk them through the logic behind your work without getting lost in jargon.
A recurring theme is that the bar shifts toward practical judgment when the role touches governance, risk, or compliance. One candidate was pressed on data governance and privacy in pipelines, plus controls-related topics, and struggled because the questions were tied to real-world policy thinking rather than generic analytics. Another candidate reported a mix of SQL, Excel, and case-style exercises, which suggests EY likes to see whether you can move comfortably between analysis and business context. Across experiences, the non-obvious make-or-break factor is domain awareness: candidates who could connect their analytics background to stakeholder communication, risk, and the “why” behind their work came across much stronger than those who only prepared for textbook questions.
Synthetized from 3 candidates reports by our editorial team.
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Real interview reports from people who went through the Ey process.
The EY interview felt much more conversational than I expected, even though it still covered a lot of technical ground. I went through an initial assessment and then an in-person interview that took about a month from application to final decision. The first round was with a senior manager, and the second was with a senior director. Both were pretty relaxed and focused on getting to know me, but they still asked enough to see whether I actually understood the work behind my resume.
A big part of the discussion was centered on Power BI and Power Query. I was asked to walk through a project, my role and responsibilities, the transformations I used, and the data sources I worked with. From there, the questions moved into Power Query basics like merge versus append, query folding, handling nulls and errors, referencing versus duplicating a query, custom columns, group by, and removing duplicates. They also drilled into Power BI concepts such as import mode versus direct query, fact and dimension tables, star schema versus snowflake schema, filters versus slicers, drillthrough versus drilldown, bookmarks, relationships, and how to optimize reports for large datasets. The DAX portion was also fairly detailed, with questions on measures versus calculated columns, SUM versus SUMX, SUMMARIZE, ALL and ALLEXCEPT, row context, and time intelligence like MTD, QTD, YTD, and SAMEPERIODLASTYEAR. On the service side, they asked about licenses, workspaces, RLS, gateways, scheduled refresh, incremental refresh, and dataflows. Even though the tone was friendly, it was definitely a real technical screen for someone claiming Power BI experience.
What stood out most was that they cared as much about how I explained my work as the exact answer. I also got the usual fit questions like why EY and why the service line, plus a few behavioral prompts about adapting when I had to do something I didn’t know how to do. I heard back about a week later and received an offer. My main takeaway is to be ready to talk through your own project end to end in Power BI, not just definitions from memory.
Prep tip from this candidate
Be ready to explain your Power BI project end to end, especially the transformations in Power Query and the data model choices behind it. Also drill the differences between import vs direct query, measures vs calculated columns, and common DAX/time-intelligence functions like SUMX, ALL, ALLEXCEPT, MTD/QTD/YTD, and SAMEPERIODLASTYEAR.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Ey
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Hurdles In Data Projects | |
| Sort Strings | |
| Classification and Regression | |
| Overfit Avoidance | |
| Stakeholder Communication | |
| Simple Explanations | |
| Why Do You Want to Work With Us | |
| Xgboost vs Random Forest | |
| Your Strengths and Weaknesses | |
| Linear vs Logistic Regression | |
| Backpropagation Explanation | |
| Experiment Validity | |
| Raining in Seattle | |
| Bagging vs Boosting | |
| Revenue Retention | |
| Using R Squared | |
| Assumptions of Linear Regression | |
| Find Duplicate Numbers in a List | |
| Missing Housing Data | |
| Data Preparation for Imbalanced Data | |
| Spam Classifier | |
| Bias vs. Variance Tradeoff | |
| FAQ Matching | |
| Multicollinearity in Regression | |
| Slow SQL Query | |
| Swap Variables | |
| String Palindromes | |
| Algorithm Reliability | |
| Youtube Recommendations |
Synthesized from candidate reports. Individual experiences may vary.
The process often starts with an HR call to confirm interest, background, and basic fit. Candidates are asked standard behavioral questions such as strengths, weaknesses, career goals, why EY, and how they handle stress or pressure.
Some candidates complete an initial assessment before the main interviews. This can include practical work-style exercises such as a case study and an Excel test, alongside early screening of analytical fundamentals.
The first substantive interview is often with a manager, senior manager, or senior developer and focuses on technical depth. Depending on the role, this can cover SQL and DBMS basics, or more role-specific analytics topics like Power BI, Power Query, DAX, report optimization, and data modeling.
A later round is conducted with managers or directors and is typically more conversational but still technical. Candidates are expected to walk through their resume and projects end to end, explain their role and decisions, and answer follow-up questions on practical implementation, domain judgment, and business impact.
After the final interview, candidates usually hear back within about a week. In the reported experiences, the process took roughly a month from application to final decision, and successful candidates received an offer shortly after the last round.