Data and analytics roles span a wide range — from BI/reporting to data science to data engineering — and interviews usually test a mix of technical tool fluency and the ability to translate data into a decision, in different proportions depending on the specific role.
The typical structure
A screen covering background and the specific tools/platforms on your resume.
A technical round — SQL, a modeling or statistics question, or a take-home analysis exercise, depending on how technical the role is.
A case or business-communication round — given a dataset or scenario, what would you look at and what would you recommend, with emphasis on how you'd explain it to a non-technical stakeholder.
A behavioral round covering how you've handled ambiguous requests or pushed back on a flawed analysis request.
What's actually being tested
Technical rounds test whether you can actually do the work with the specific tools the role uses — the exact stack varies a lot (SQL and a BI tool for reporting-heavy roles; Python, modeling frameworks, and statistics for data science; pipeline and orchestration tools for data engineering). Case rounds test something different: whether you can turn a messy question into a structured analysis and communicate the result clearly, which matters just as much as technical correctness in most data roles.
How to prepare
Identify from the job description which flavor of data role this actually is, and weight your prep toward that (don't over-prep deep ML theory for a reporting-heavy BI role, or vice versa).
Practice explaining a past analysis to a non-technical audience in plain language — this is tested more often than raw technical depth in many data interviews.
Prepare a real story about pushing back on or clarifying an ambiguous data request, since it's a common behavioral prompt in this field.
KrackerAI builds technical questions from the specific data tools and platforms your target job description names, and behavioral questions grounded in your actual project history — so prep matches whichever flavor of data role you're actually interviewing for.