A Data Analyst role at EY sits between technical skill and client communication, and the interview reflects that. You will be tested on SQL, Excel, data visualisation and business reasoning, alongside behavioural fit. This page explains the rounds, the analytical questions that recur, what interviewers look for, and how to prepare so you can turn data into a story.
Start a free mock interview →EY's brand is built on assurance, tax, strategy and transactions, and EY-Parthenon handles the strategy-heavy cases, so the flavour of a case depends heavily on which service line you apply to.
The process generally starts with a screen and an online assessment - aptitude, and sometimes a SQL or case test - followed by two to three interviews. Rounds cover technical data skills, a business or case scenario, and behavioural fit, usually finishing with a manager or partner conversation.
EY commonly runs an assessment day with a group exercise, a case and a partner interview, and watches how you contribute to a team under time pressure. The signal EY wants is an analyst who is technically sound and can translate analysis into a recommendation a client will act on.
Prepare across the analyst toolkit:
A strong answer to a case like sales dropped last quarter - investigate segments the data by region, product, channel and customer type, separates a real drop from a data issue, forms a hypothesis, and states a clear next step. Weak candidates list charts without a hypothesis or bury the recommendation at the end.
At EY, an analyst who cannot explain findings to a non-technical stakeholder is only half useful, so communication is tested directly. Expect prompts like explain a complex analysis to a client with no data background. Behavioural questions cover teamwork under deadline, attention to detail and why EY. Use STAR and quantify impact where you can. EY frames fit around its purpose - building a better working world - and looks for genuine, values-led motivation.
Partners look for someone who is careful with data, honest about limitations, and able to turn numbers into a decision - the qualities that make a client trust your dashboard rather than second-guess it. This blend of SQL fluency, clean framing and business communication is what employers screen for across Data Analyst / Data Science Jobs, so the reps transfer well beyond a single firm.
Beyond querying, EY interviewers probe whether you reason soundly about data. Be ready for light statistics - averages versus medians and when each misleads, the difference between correlation and causation, sample size intuition, and how you would spot a data-quality problem before it reaches a client deck. You do not need advanced modelling, but shaky fundamentals here undermine trust in everything else you present.
A strong candidate names caveats without prompting: this trend is based on two weeks of data, this segment is small, this metric changed definition mid-year. That instinct to caveat honestly is a large part of what distinguishes a reliable analyst from a fast one.
EY data analysts frequently support assurance and consulting engagements with analytics, so interviewers look for someone who can move from a client question to a clean, defensible analysis. Be ready to discuss a project where your data work changed a decision, and to explain a technical result simply - EY prizes the ability to communicate insight to partners and clients without jargon.
Convert study into reps:
InterviewPrep's free AI voice mock interview builds a session from your CV and a EY Data Analyst job description, then scores your answers, pace and filler words - a good way to practise narrating a case and explaining analysis clearly before the real rounds.
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