Barclays data engineer interviews reported by candidates mix SQL, Spark or pandas, data structures, resume deep dives, and behavioral questions. Experiences vary widely: two candidates got no offer and one received an offer.
$126K
Avg. Base Comp
$147K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe Barclays data engineer interviews as SQL-centered, with coding and behavioral questions around it. All three reports mention SQL in some form: window functions in one, joins in another, and SQL problems solved in both pandas and Spark in a third. SQL fundamentals are the most consistent thread, so be ready to explain joins and window functions clearly and not just write them.
One candidate reported a technical and behavioral round followed by a 45-minute panel, with roughly 13-15 back-to-back behavioral questions, two DSA problems, AWS questions, and a scenario about diagnosing latency in a pipeline that had run smoothly for two years before degrading. Another reported a technical assessment, then a technical interview with a graph shortest-path problem and SQL joins, then an HR round on handling messy, unstructured data. That candidate received an offer.
Resume depth matters. Interviewers reportedly asked about day-to-day responsibilities and technical decisions, so prepare concrete project stories covering what you built, why, and how you handled failures or data quality problems.
Format can differ from what you are told. One candidate for an ETL and regulatory reporting role expected a competency interview but described unrelated technology questions and an interviewer joining unannounced. Confirm the format and panel with your recruiter, and be ready to steer back to your own experience. With only three reports, treat these as individual accounts.
Synthesized from 3 candidate reports by our editorial team.
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Real interview reports from people who went through the Barclays process.
I interviewed for a Data Engineer role at Barclays through Grace Hopper Celebrations 2024. The process consisted of an initial phone screen, followed by a technical and behavioral interview round, and then a 45-minute panel interview with a mix of behavioral and technical questions anchored to my resume and work experience.
The technical portion covered AWS services, SQL problems (which I had to solve using both pandas and Spark), and two DSA problems. Beyond coding, there were scenario-based questions—one that stood out asked how I'd diagnose latency in a data pipeline that had been running smoothly for two years but suddenly started degrading. They also grilled me extensively on my resume, asking about my day-to-day responsibilities and diving into the technical decisions I'd made. The behavioral side was heavy, with roughly 13-15 questions fired at me back to back, and a final situational prompt about designing a data engineering pipeline from scratch.
What was frustrating was the overall process experience. Communication from recruiters was poor, and there was little respect for candidates' time—interviews started late, and the energy felt disorganized. During the panel round, only one of three interviewers was genuinely engaged; another had connectivity issues and kept dropping out, while the third stayed muted throughout due to background noise. The questions themselves were fairly generic—database optimization, CI/CD platforms, API development, Ansible, FastAPI—without much depth or follow-up to understand my thinking. By the end, it felt like they were checking boxes rather than having real conversations about fit or growth.
Prep tip from this candidate
Expect deep dives into your resume and production troubleshooting scenarios—prepare specific examples of diagnosing performance degradation and failures in systems you've built. Have your SQL optimization and Spark/pandas transformations sharp, since both appeared across multiple rounds.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Barclays
Select the 2nd highest salary in the engineering department
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter or phone conversation before the main interviews. One candidate was told the next round would be competency-based, so it is worth asking the recruiter to confirm the format and who will interview you.
One candidate reported a technical assessment that had to be passed before interviews. Another reported a combined technical and behavioral round early on. The exact content likely varies by team, so prepare SQL and basic coding broadly.
Candidates report SQL joins and window functions, SQL solved with pandas and Spark, graph shortest-path and other DSA problems, and AWS questions. One also described a scenario on diagnosing a slowly degrading pipeline, so practice explaining your debugging approach.
One candidate reported a 45-minute panel mixing behavioral and technical questions based on their resume, including many rapid behavioral questions. Another reported an HR round on messy, unstructured data and ambiguity. Expect to discuss your projects in detail.
