Data Analyst
115SQL, grain, a BI tool, and the nerve to say the number is wrong.
SQL · Metrics · BI · Behavioral
Interview prep
The data interview is several interviews.
SQL, modeling, pipelines, experiments, system design, and behavioral — the mix changes by role. All nine DataLane roles sit a SQL pad. Prep the loop you will actually walk, not two stacks and a hope.
- 310
- Questions
- 9
- Role tracks
- 27
- SQL coding labs
- 127
- Companies named
From the bank
- Capital OneSQLmedium
A join exploded revenue. How do you find the grain mismatch in five minutes?
- MetaSQLmedium
Running total of daily revenue. Why is SUM(SUM(amount)) OVER (...) valid?
- SnowflakeSQLmedium
QUALIFY vs a CTE for window filters — when do you use each?
- GoogleSQLmedium
A query is correct but scans last year. How do you prove partition pruning?
- MetaSQLmedium
You need a 7-day rolling unique users. What breaks if you use COUNT DISTINCT in a window carelessly?
Pick the role you want next
Each track is a sequence, not a pile of unrelated cards. Same nine roles as the roadmaps and coding hub — original DataLane questions, not a third-party dump.
BI Analyst
124Warehouse SQL at dashboard grain. Serving layers that are not your OLTP.
SQL · Warehouse · Trino / CH · Modeling
dbt models, tests, CI, and a metric someone in finance can trust.
SQL · dbt · Modeling · Quality · Behavioral
SQL, pipelines, warehouses, streaming, and the platform sketch they ask at 3pm.
SQL · Python · Orchestration · Streaming · System design · Behavioral
SQL for features, stats without vibes, and a holdout you would defend.
SQL · Python / stats · Modeling · Experiments · Behavioral
ML Engineer
155Train, serve, and rollback. Features as tables. Latency as an SLA.
Python · Features · Serving · System design
Gates, rollback, and the SQL that proves training and serving agree.
Quality SQL · Eval · Serving · System design
AI Engineer
155RAG as ETL, feature tables without leakage, and Cortex as a transform.
SQL · Python · RAG / features · Streaming · System design
Grain, cost, and paved roads. You still have to query the mart you designed.
SQL · Warehouse · System design · Cloud · Behavioral
Python and SQL in one hub
Python problems switch NumPy, Python, or PyTorch from a dropdown. SQL problems use the same sample warehouse as the sandbox — 27 queries graded check by check.
Or pick a stack
20 stacks. Filter below, then drill one topic.
SQL21 questionsWindows, grain, and the query you can defend on a whiteboardSnowflake19 questionsCredits, Time Travel, and warehouses you can explain to FinOpsdbt16 questionsStaging, marts, tests, and CI that does not rebuild the warehouseAirflow16 questionsIdempotent DAGs, catchup, and why XCom is not a data busDatabricks16 questionsDelta, medallion, and the lakehouse questions platform teams askKafka16 questionsPartitions, consumer groups, and the streaming trade you can defendSpark15 questionsJobs, shuffles, and the PySpark questions that show you have shippedAWS16 questionsS3, Glue, Athena, Redshift — pick the service in sixty secondsAzure16 questionsADF, Synapse, Fabric — who owns the pipeline on a Microsoft stackBigQuery15 questionsBytes scanned, partitions, and slots — the GCP warehouse screenPython & modeling18 questionsQuality checks, SCD, grain — the language plus the warehouse designAI / RAG / MLOps18 questionsRetrieval, features, and the boundary between DE and MLSystem design22 questionsEnd-to-end platforms: grain, SLAs, CDC, lakes, and what you page at 3amDagster11 questionsAssets, checks, and why the DAG is a data graphApache Flink11 questionsEvent time, watermarks, and what exactly-once actually meansTrino11 questionsFederated SQL that can melt the source if you are carelessClickHouse11 questionsMergeTree, ORDER BY, and why tiny inserts diePostgreSQL11 questionsThe OLTP source: CDC, EXPLAIN, and do not scan prodData quality13 questionsContracts, freshness, and when to fail the jobBehavioral18 questionsSTAR stories for incidents, grain fights, cost, and saying no
This week in screens
Themes people are discussing in public. We do not scrape LinkedIn.
2026-08-28 · Coinbase · Ledger grain
A deposit webhook retried. How do you not mint two ledger rows?
Idempotency key (or natural key on payment_id + event_type) and an upsert. A running-balance column you overwrite is not a ledger.
Practice sql →2026-08-26 · Apple · Shared lake, one writer
Two engines must share one lake table. What do you refuse to do?
Dual-write CSV or two independent Delta copies. Pick Iceberg (or UniForm) with a single writer. Two writers is how the copies lie.
Practice system-design →2026-08-22 · LinkedIn · Rebalances under load
Your consumer group rebalances every few minutes during peak. What do you check first?
max.poll.interval.ms vs processing time, cooperative sticky assignment, and whether a slow partition (hot key) is triggering leave/join. Adding consumers without fixing poll interval often makes lag worse.
Practice kafka →2026-08-18 · Snowflake · Cortex in a dashboard
A hiring manager asks you to put Cortex COMPLETE in a Looker explore. What do you say?
No. Materialize the label in ELT once, version the prompt, and let BI read a column. Dashboard refresh is a token bill and a non-deterministic metric.
Practice snowflake →2026-08-10 · Capital One · Fan-out revenue
Revenue doubled after a “harmless” dimension join. How do you prove it in five minutes?
Row counts before and after the join, then GROUP BY the join key HAVING count(*) > 1 on the dimension. Fix the grain or aggregate the dim. Never DISTINCT the fact.
Practice sql →
By company
Publicly discussed screen shapes. Updated 2026-08-28.