Fidelity Investments Data Analyst interviews reported here range from a SQL-and-Excel assessment and panel to recruiter, manager, team, leadership, and presentation-based conversations.
$112K
Avg. Base Comp
$152K
Avg. Total Comp
2-5 rounds
Typical Rounds
2-4 weeks
Process Length
Fidelity Investments Data Analyst candidates describe several interview paths rather than one fixed sequence. One candidate completed an online SQL-and-Excel assessment with multiple-choice items followed by two SQL coding questions, then met an online panel that included recruiting and project leadership. That panel asked how the candidate had debugged code and worked with diverse stakeholders. Another candidate recalled a simple question about explaining a left join during a recruiter-to-manager-to-team-to-VP process.
Clear communication about analysis is as prominent as technical recall in these reports. One process included a short slide presentation that asked the candidate to synthesize a dataset for an executive audience; its later conversations were panels with stakeholders or adjacent leaders. In a separate two-round account, the technical discussion centered entirely on projects listed on the resume, including the candidate's role and decisions, before an HR conversation asked why the company should hire them.
Prepare SQL both as explanation and live problem solving, but also rehearse how you turn data into a concise business story. Have specific examples ready for debugging, collaboration, and the choices behind your own projects. Interview formats vary across these accounts, so treat the reported stages as possible paths rather than a single standard process.
Synthesized from 5 candidate reports by our editorial team.
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Real interview reports from people who went through the Fidelity Investments process.
The process started with a behavioral phone screening, which felt straightforward and conversational. After that, I went in person for the technical rounds. What caught me off guard was the structure—I interviewed with two different people in separate rooms. The first was a branch manager who dug into behavioral questions using the STAR method, asking me to walk through specific situations I'd handled. The second round was with a developer who focused on technical skills pulled directly from my resume and projects.
The technical interview covered SQL and DSA questions at a medium difficulty level. I got questions on writing SELECT statements to handle specific database scenarios, and some algorithm problems that felt like LeetCode medium material. There was also a project-based component where I had to discuss and explain work I'd done. The whole day felt long—there was definitely downtime between rounds—but the interviewers were respectful and engaged, which made it less stressful than I expected.
The entire process moved quickly overall. From application to offer, it took about three weeks, which was faster than the typical two and a half months I've heard others mention. HR was responsive throughout, and I never felt left hanging. The key takeaway for me was preparing with the STAR method for behavioral questions and having solid SQL fundamentals ready. They really did care about understanding both who you are and what you can do.
Prep tip from this candidate
Use the STAR method to structure behavioral answers clearly, and brush up on SQL SELECT statements for specific use cases—avoid generic query knowledge and focus on practical database problem-solving.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Fidelity Investments
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Fractional Shares | |
| Google Maps Improvement | |
| Hurdles In Data Projects | |
| Out of Stock Inventory | |
| RAG Strict Source Control | |
| Slow SQL Query | |
| The Longest Journey | |
| Loan Model | |
| Seller Type Modeling | |
| Testing Constraints | |
| Client Solution Pushback | |
| Interest Rates | |
| WallStreetBets Sentiment Analysis | |
| Reddit-like Notifications | |
| Empty Neighborhoods | |
| Rolling Bank Transactions | |
| Employee Salaries | |
| Comments Histogram | |
| Closest SAT Scores | |
| Top Three Salaries | |
| Monthly Customer Report | |
| Slacking Employees Salaries | |
| Experiment Validity | |
| 500 Cards | |
| Find the Missing Number | |
| Compute Deviation | |
| Bagging vs Boosting | |
| Subscription Overlap | |
| Maximum Profit |
Synthesized from candidate reports. Individual experiences may vary.
One candidate first completed an online assessment covering SQL and Excel. It began with multiple-choice questions and then required two SQL coding questions, so candidates may need to move from quick concept recognition to writing working queries.
Candidates report recruiter-led conversations in some paths. In another account, a technical conversation instead focused on resume projects, including the candidate's role, work, and reasoning, before an HR discussion.
Reported panels varied: one included recruiting and project leadership, another involved stakeholders or adjacent leaders, and a separate account described manager, team, and VP conversations. Behavioral discussion may cover debugging code and collaborating with diverse stakeholders.
One candidate was asked to prepare a short sample slide presentation that synthesized a dataset for an executive audience. Candidates may be expected to explain the business story and communication choices, not only the underlying analysis.
