Irly Data Analyst interview typically runs 3 rounds: HR screening, technical case, manager fit interview. It usually takes about 2-3 weeks and is notably case-heavy with follow-up probing.
$80K
Avg. Base Comp
$100K
Avg. Total Comp
3
Typical Rounds
2-4 weeks
Process Length
We’ve seen Irly evaluate Data Analyst candidates less like pure SQL operators and more like junior consultants who can turn messy data into a client-ready story. Multiple candidates reported that the strongest signal was not whether they could write a query quickly, but whether they could spot data-quality traps like duplicates and NULLs, avoid double-counting, and explain why the logic behind the metric mattered as much as the syntax. That tells us Irly is looking for analysts who are careful with definitions and comfortable defending their numbers under pressure.
A recurring theme is the business case: when a KPI or revenue drops, they want a structured investigation, not a scattershot list of metrics. Our candidates report being pushed to clarify the problem, form hypotheses, choose the right cuts of the data, and then translate findings into recommendations. The follow-up questions seem designed to separate people who can name KPIs from people who can actually reason through what changed and why.
We also see a strong emphasis on communication in a consulting context. Candidates were asked how they’d build dashboards for management and how they’d explain results to non-technical stakeholders without overcomplicating things. In practice, that means Irly seems to value analysts who can move comfortably between SQL, business judgment, and client-facing explanation — especially when the data is imperfect and the answer isn’t obvious.
Synthesized from 1 candidate report by our editorial team.
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Real interview reports from people who went through the Irly process.
From what I remember, the process had three rounds, but the technical case was the main one.
The first round was with HR and was mostly about my background, why I wanted consulting / banking, my salary expectations, notice period, and my level in SQL / BI tools. Pretty standard overall.
The second round was the most useful one to prepare for. I got a small use case with SQL + business reasoning. On the SQL side, they gave me a few tables and asked me to write joins / aggregations and calculate KPIs. What stood out is that there were some data-quality traps, so they cared as much about the logic as the syntax. Then there was a more business-oriented case around how I would investigate a drop in a KPI / revenue and what data I would look at first. They really wanted a structured approach: clarify the problem, form hypotheses, check the right cuts of the data, and turn it into recommendations.
The last round was more with a manager and focused on fit: past projects, stakeholder management, handling ambiguity, and how I explain analysis results to non-technical people.
Overall, it felt less like an academic test and more like: can this person do solid SQL, think through a business problem, and communicate clearly enough to work with a client.
Questions asked: From what I remember, the technical round was a mix of SQL, dashboard thinking, and business reasoning.
On the SQL side, they gave me a small dataset with a few tables and asked fairly classic things: write joins, calculate KPIs by segment, and explain how I’d avoid double-counting or bad results if the data had duplicates / NULLs. I also remember at least one question where the point wasn’t just to get the query right, but to explain the logic behind it.
The case part was more like: “A banking KPI has dropped / revenue is down / customer activity is lower than expected — how would you investigate it?” They wanted a structured answer: what questions I’d ask first, what hypotheses I’d test, what cuts of the data I’d look at, and how I’d turn that into recommendations for the client.
There was also a dashboard / reporting angle. I was asked what I would put on a dashboard for management, which KPIs I’d prioritize, and how I’d present the results to a non-technical stakeholder without making it too complex.
I don’t remember any especially weird take-home assignment, but the main difficulty was that they kept pushing with follow-up questions to see whether I was just naming metrics or whether I could actually reason through the problem like a consultant.
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Synthesized from candidate reports. Individual experiences may vary.
The first round is a standard HR conversation focused on your background, motivation for consulting or banking, salary expectations, notice period, and your comfort level with SQL and BI tools. It is mostly an introductory fit check and a chance for the company to confirm basic role alignment.
This is the main round and combines SQL with business reasoning. You may be given a small dataset and asked to write joins, aggregations, and KPI calculations while being careful about duplicates, NULLs, and other data-quality traps. The same round also includes a business case such as investigating a drop in revenue or a KPI, plus questions about dashboard design and how you would communicate findings to management.
The final round is with a manager and focuses on fit and working style. Expect questions about past projects, stakeholder management, handling ambiguity, and explaining analysis results to non-technical stakeholders in a clear, client-friendly way.
