Exl Business Intelligence interview typically runs 3 rounds: group manager, technical round, project manager. The process usually takes a few weeks and is highly technical with poor coordination.
$100K
Avg. Base Comp
$121K
Avg. Total Comp
3
Typical Rounds
2-4 weeks
Process Length
Our candidates report that Exl treats Business Intelligence like a hands-on architecture role, not a reporting job. The strongest signal is how often the conversation moves beyond dashboards into Power BI internals, data warehousing, and Microsoft Fabric. One candidate was pressed on advanced DAX, workspace security, governance, Tabular Editor, and even the distinction between Lakehouse and Data Warehouse concepts, which tells us the team wants people who can reason about the stack end to end, not just build visuals.
A recurring theme is that Exl seems to value practical judgment as much as technical depth. The lighter business-focused discussion with a project manager suggests they still care about how someone translates requirements, but the technical rounds clearly dominate the evaluation. We’ve seen that candidates who can explain why a model or workspace is structured a certain way tend to stand out more than those who only know feature names. In other words, implementation choices and tradeoffs matter here.
The other pattern our candidates mention is less about the interview itself and more about the process around it: coordination can be shaky. In one experience, HR moved ahead with document collection and salary alignment before the final decision was truly settled, then the role was reopened after a client requirement change. That doesn’t change the technical bar, but it does mean candidates should pay attention to how firm the offer is before sharing sensitive paperwork.
Synthesized from 1 candidate report by our editorial team.
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Topics based on recent interview experiences.
Featured question at Exl
Select the 2nd highest salary in the engineering department
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| Employee Salaries | |
| Size of Joins | |
| Bagging vs Boosting | |
| Hurdles In Data Projects | |
| P-value to a Layman | |
| Duplicate Rows | |
| Type-ahead Search | |
| Precision and Recall | |
| Swap Variables | |
| Target Indices | |
| Assumptions of Linear Regression | |
| Type I and II Errors | |
| Data Preparation for Imbalanced Data | |
| SARIMA in Retail Forecasting | |
| Multicollinearity in Regression | |
| Overfit Avoidance | |
| Random Forest from Scratch | |
| Credit Card Fraud Model | |
| Explaining Linear Regression to Different Audiences | |
| Your Strengths and Weaknesses | |
| Branch Sales Pivot | |
| Correlation in Regression | |
| Linear vs Logistic Regression | |
| Random SQL Sample | |
| Booking Regression | |
| WAU vs Open Rates | |
| Success Measurement | |
| Lasso vs Ridge | |
| Netflix Churn Prediction |
Synthesized from candidate reports. Individual experiences may vary.
The first round is a mixed technical and business discussion with a group manager. Candidates should expect questions on SQL, Power BI, data warehousing, and Microsoft Fabric rather than a light screening conversation.
This is the most technical round and goes deep into the BI stack. Topics include advanced Power BI concepts, Tabular Editor, workspace architecture, security, data governance, advanced DAX, and Fabric concepts such as the difference between Data Warehouse and Lakehouse.
The final interview is with a project manager and focuses more on business logic and project management. Compared with the earlier rounds, this stage is lighter and more oriented toward how the candidate would work in delivery and stakeholder-facing situations.
After clearing the interviews, HR may confirm selection and discuss salary expectations. In this experience, the candidate was asked to upload sensitive documents to the portal before the offer letter was finalized, and the process later stalled due to a client requirement change.
