Evaluate your SQL, Python, Design, AI Engineering & Communication skills.
Pick a section and start. Every attempt draws a fresh random set from a curated pool, so retakes stay useful — and SQL and Python code runs in your browser. No sign-up, no backend. How it works.
SQL
Joins, aggregation, window functions, CTEs, transactions, indexing, and query reasoning. Code questions run in an in-browser PostgreSQL (PGlite).
Python
Idioms, data model, comprehensions, decorators, async, the stdlib, and the data stack. Code questions run in Pyodide with auto-pass/fail tests.
Data & System Design
Dimensional modeling, SCDs, partitioning, CDC, streaming, idempotency, and scale tradeoffs. Senior-level judgement.
2026 Hot Topics
Storage Lens & FinOps, Iceberg catalogs & partitioning, skew, streaming & CDC, schema & contracts, lineage, security, metadata, event-driven, vector infra and data mesh — the senior/staff concepts behind the 2026 Hot Topics deep-dives.
AI Engineering
LLM fundamentals, tokens & context windows, prompt & context design, RAG, embeddings & vector DBs, tool-calling, agents, evaluation, cost optimization, guardrails & security, and production AI architecture — the applied-AI questions now asked across engineering, data and product interviews.
Communication
Clear, globally-understood professional English — grammar & usage, interview answers, workplace conversations, email & chat, standups, explaining technical concepts, feedback, conflict, incidents, cross-cultural and executive communication. Rewrite and scenario exercises self-rated against a model answer.
Refine this check Full pool · all companies
Target specific companies
Pick one or more companies and your SQL or Python check is drawn only from real, company-tagged interview questions. Leave it empty for the standard topic-randomized check. Design and 2026 Hot Topics have no company data, so they always run topic-randomized.
Refine the question pool
Drill exactly what you want. Difficulty and format start fully on — click a chip to drop it ("tricky" lives in Hard; drop Multiple-choice to skip pure-theory recall and keep the hands-on Code and Open-ended questions). Topics start empty — add any to focus a section on those subject areas. Each section card shows the resulting pool size.
Format and topic filters apply to the topic-randomized pool — company-tagged SQL & Python questions come from a separate code-only bank, so only Difficulty narrows those.
How it works
- Each attempt draws a fresh random set of 20 questions from the section pool, with options shuffled — repeats and memorization don't help.
- Company mode (SQL & Python) — open Refine this check below the section cards, pick one or more companies, and the quiz is drawn from a pool of real, company-tagged interview questions instead of the topic pool. Those questions are self-rated against a model answer.
- Refine the pool — the same panel narrows every section by difficulty, format and topic. Drop Multiple-choice to skip pure-theory recall; keep Hard for the tricky ones; add topics to focus on specific areas. Each section card shows the filtered pool size live.
- Objective questions (single / multi) are auto-graded the moment you submit.
- SQL code runs against a preloaded PostgreSQL schema in your browser (PGlite, ~14 MB on first run — cached afterwards); result table is checked against an expected output.
- Python code runs in Pyodide (CPython 3.12 / WASM); a hidden test harness reports pass/fail. First load is ~6 MB.
- Open-ended answers reveal a model solution and key-points checklist — you self-rate Missed it / Partial / Got it.
- Every visit is a clean slate — submitted attempts don't persist; landing here always starts a new draw.
- Mid-quiz reload-safe — accidental refresh while answering keeps your in-progress answers, but a finished attempt won't follow you back.