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QSWEQB

Data Engineer

Pipelines, Spark and warehousing, SQL depth, and the modelling and orchestration questions specific to data platforms.

The loop, in order

  1. Data & AI Engineering13 questions · 8 topicsQuestions for data engineering, ML engineering, and the LLM-application roles now appearing in mainstream hiring loops.
  2. Databases & SQL13 questions · 8 topicsQuery-writing rounds and the storage-engine reasoning behind why a query is slow, for backend, data, and DBA roles alike.
  3. Python12 questions · 7 topicsPython for backend, automation, and data roles, including the runtime behaviour that surprises candidates who only know the syntax.
  4. DevOps & Cloud13 questions · 8 topicsPlatform and infrastructure questions for DevOps, SRE, and any backend role expected to own its service in production.
  5. Behavioural & Culture Fit13 questions · 8 topicsThe round candidates most often under-prepare, treated as a skill with structure rather than small talk, including the rubric interviewers score against.
  6. HR, Screening & Offer12 questions · 6 topicsThe recruiter and HR rounds that gate the technical loop and decide your compensation, where most candidates improvise and lose money.
  7. Banking & Financial Services16 questions · 11 topicsHow a bank works underneath the app: the ledger that must always balance, the rails money moves over, the identity and financial-crime controls wrapped around it, and the regulatory reporting that constrains every design decision.
  8. E-commerce & Retail14 questions · 9 topicsThe path from browse to delivered and back again, where inventory is the central consistency problem and every edge case is a real order belonging to a real person.

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