winkle
Back

Interview · Technical

Data engineer

Covers pipeline design, warehouse modelling, data quality, performance and handling personal data. Suits mid to staff-level data and analytics engineers. Follow-ups push for failure handling, real data volumes and how problems get caught before users see them.

Suits: Data engineer, Analytics engineer, Big data engineer, ETL developer

Questions
7 of 17
Length
35 min
Format
Voice or typed
Levels
Mid to Staff
See this interview on a 30-minute call.
AI interviewerScored
Example

  1. Interviewer: Tell me about a time you changed someone's mind at work. How did you go about it?

  2. Candidate: Our team wanted to rebuild the billing page from scratch, and I thought it was the wrong call, so we put together a plan to…

  3. Follow-up

    Interviewer: You said "we". What did you say yourself, and what finally changed their mind?

  4. Scored on

    • Pipeline design30%
    • Data modelling25%
    • Reliability and data quality25%
    • Trade-offs and collaboration20%

    Score, reasons and recording. Your team decides.

An example exchange. This interview's own questions open when you use it.

What it listens for, and how much each part counts.

Every answer is scored against this guide, with the reasoning written beside the score. You get the recording or the written answers too, and your team makes the call.

  • Pipeline design30%
    Builds pipelines that are incremental, re-runnable and fit the need.
  • Data modelling25%
    Models data so it is clear, correct and easy to query.
  • Reliability and data quality25%
    Catches failures and bad data before users do.
  • Trade-offs and collaboration20%
    Weighs cost, speed and effort and works well with other teams.

Send it alongside

All interviews

  • Data analyst case

    Data · Technical

    One booking drop, worked to a recommendation, showing how an analyst frames, slices and advises.

    Listens for

    • Clarifying and framing
    • Analytical approach
    • Technical accuracy
    • Recommendation and communication
    Voice or typed

    7 stages · 40 min · Junior to Senior

  • Data analyst

    Data · Technical

    Finds out how a candidate turns messy questions and data into sound answers people act on.

    Listens for

    • Analytical reasoning
    • SQL and data handling
    • Statistical judgement
    • Communication and impact
    Voice or typed

    7 of 18 questions · 35 min · Junior to Senior

  • Data scientist

    Data · Technical

    Finds out how a candidate frames problems, models with rigour and proves real-world impact.

    Listens for

    • Problem framing
    • Statistical and modelling rigour
    • Experimentation and causal reasoning
    • Communication and impact
    Voice or typed

    7 of 17 questions · 35 min · Mid to Staff