Data Engineering Interview Practice
A data engineering interview loop is usually 5 rounds across 2 days: SQL screen, then SQL + Python + modeling + design + behavioral as an onsite block, then a hiring manager call. Most prep covers 1 round well and the others poorly. The full-loop simulator runs every round, with the rubric calibrated by company. Pick a target company, pick a seniority level, walk the full loop.
A data engineering interview loop is usually 5 rounds across 2 days: SQL screen, then SQL + Python + modeling + design + behavioral as an onsite block, then a hiring manager call. Most prep covers 1 round well and the others poorly. The full-loop simulator runs every round, with the rubric calibrated by company. Pick a target company, pick a seniority level, walk the full loop.
Know the patterns before the interviewer asks them.
Anatomy of a standard senior DE loop
Frequency is share of senior loops that include the round; surface is the page on this site that practices it.
RECRUITER SCREEN 30 min
────────────────────────────────────
behavioral, why this company ─► /behavioral-interview-questions
salary expectations
next step + timeline
│ pass
▼
HIRING MANAGER SCREEN 45 min
────────────────────────────────────
domain experience, project depth 95% of loops
fit with team's tech stack
│ pass
▼
┌─── ONSITE BLOCK (2 days or single day) ───┐
│ │
│ SQL TECHNICAL 45 min 95% ─► /sql-practice-online │
│ PYTHON TECHNICAL 45 min 78% ─► /python-coding-practice │
│ DATA MODELING 45 min 65% ─► /data-modeling-interview-practice │
│ SYSTEM DESIGN 60 min 52% ─► /system-design-interview-practice │
│ BEHAVIORAL 45 min 100% ─► /behavioral-interview-questions │
│ │
└────────────────────────────────────────────┘
│ debrief, leveling
▼
OFFER OR REJECTCompany-specific tracks
What each named company tests, drawn from verified interview write-ups. Full company guides at /companies have more detail.
6-week prep allocation by surface
Problem volume per surface per week. The stack composition shifts as you move from foundations to mocks.
Behavioral stories every DE candidate needs
6 themes that map to most DE behavioral prompts. Each theme needs 1-2 STAR-format stories with concrete numbers.
| Theme | What the interviewer is listening for |
|---|---|
| Scoped a project under ambiguity | Specific business question, the data you had vs needed, the call you made, the outcome. |
| Disagreed with a senior engineer or PM | What the disagreement was, how you escalated, the resolution, what you'd do differently. |
| Recovered from a production incident | What broke, your role in detection vs fix, the root cause, the post-mortem item. |
| Pushed back on scope | What was asked, why it didn't fit, what you proposed instead, how it landed. |
| Built or led a hiring process | What you screened for, a tradeoff you made, the result, your evolution as a hiring lead. |
| Owned a metric that moved | The metric, the baseline, what you changed, the measured impact, the second-order effect you noticed. |
DE interview practice FAQ
What's the difference between this and solo problem practice?+
Do you cover the data modeling round?+
Are there company-specific tracks?+
What if I'm transitioning from analyst or software engineer?+
How is the catalog calibrated to real interviews?+
What about take-home assignments?+
How much prep do I actually need?+
Start with the SQL screen mock
- 01
Active recall beats re-reading by 50%
Cognitive-science meta-reviews (Dunlosky et al., 2013) rank practice testing as a top-tier study technique, while re-reading and highlighting rank near the bottom
- 02
76% of hiring managers reject on the coding task, not the resume
From HackerRank's 2024 Developer Skills Report. Candidates who look strong on paper still fail the live screen if they haven't done timed, executable practice
- 03
Five problem shapes cover 80% of data engineer loops
Dedup, sessionization, top-N-per-group, slowly-changing dimensions, partition tricks. Writing the shapes by hand turns the unfamiliar into pattern recognition