Candidates describe a Morgan Stanley Data Engineer process that opens with an online assessment, then moves to technical interviews covering SQL, Python, Spark and Azure. Both reports ended without an offer.
$142K
Avg. Base Comp
$209K
Avg. Total Comp
3 rounds
Typical Rounds
2 weeks
Process Length
Two candidates who interviewed for Morgan Stanley data engineering roles describe a process that starts with an online screen and then gets steadily more technical. Both were rejected, and each named a gap they wished they had closed beforehand.
The first stage is an online assessment. One candidate got SQL and Python logic questions, including deleting duplicate rows from a table and tracking student absences across consecutive days. Another described an aptitude and logical reasoning section bundled with a medium-difficulty coding test. Practice deduplication, consecutive-event and edge-case SQL so you can work through these quickly.
The technical interviews then go deeper. One candidate was asked about projects, tech stack, DSA level, core Python and SQL optimization, with Azure raised because the role involves cloud work. The same candidate's later round covered Apache Spark and Azure architecture, Flask, and a coding problem on sorting duplicate logs by timestamp. The other candidate got a verbal sliding-window problem, questions on Python, SQL and Scala, and math topics such as matrix rank, probability and statistics. That candidate was also asked why they wanted Morgan Stanley and its IED program.
The pace reported by one candidate was about two weeks across three rounds, with results back within a few days of each stage. Both candidates described the interviewers as professional and calm. Prepare to talk through your reasoning out loud, and review Spark fundamentals, Azure services and basic linear algebra and probability, since those were the areas the candidates said they wished they had studied more.
Synthesized from 3 candidate reports by our editorial team.
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Synthesized from candidate reports. Individual experiences may vary.
Candidates report an online screen that mixes SQL and Python logic questions. One described deleting duplicate rows and tracking absences over consecutive days. Another described aptitude, logical reasoning and a medium-difficulty coding test. Expect to handle edge cases carefully, and note that the format may vary by program.
Candidates report interviewers digging into projects and tech stack, core Python, SQL optimization and data structures, and sometimes Azure. One candidate got a verbal sliding-window problem and was asked to think aloud. Math questions on matrix rank, probability and statistics also came up in one report.
One candidate reports a later round focused on Apache Spark, Azure cloud architecture and Flask. It also included a coding problem on duplicate logs that had to be sorted by timestamp, which tested handling of messy real-world data. This round may differ by team, so confirm the focus with your recruiter.
One candidate was asked why they were interested in Morgan Stanley and the IED program specifically. The tone was described as calm and professional rather than aggressive. Applicants should typically prepare a clear, specific answer on motivation and how they approach problems.
