Design a data catalog and lineage system
PremiumData pipelineMedium
- Data catalog
- Data lineage
- OpenLineage
Quick answer
This data pipeline interview question asks you to design a data catalog and lineage system. Aim for a design that moves data from sources to consumers reliably and on time, then explain ingestion, processing, storage and trade-offs. Interviewers want to see how you handle volume, late or bad data and failures along the way.
The problem
Design a data catalog and lineage system: one place where engineers search 500,000 datasets, see owners, schemas and PII tags, and follow column-level lineage from source tables to dashboards. Metadata flows in from the warehouse, lake, Kafka, BI tools and job runs. The hard parts are fresh metadata, SQL parsing and fast impact queries.
Teams ask questions like who owns this table, can I drop this column, and which dashboards break if this job fails. Today they ask in chat and guess.
What must a data catalog and lineage system do?
- Lineage: Show table- and column-level lineage upstream and downstream across warehouse SQL, Spark jobs, Kafka topics and dashboards.
- Search: Find datasets by name, column, description, tag and owner, ranked by usage.
How well must it do it?
- Freshness: New tables are searchable within 15 minutes; lineage updates within 1 hour of a job run.
- Impact query speed: A 10-hop downstream query answers in under 2 seconds.
What scale should you design for?
Use these numbers in your estimates.
The scale numbers unlock with this questionUnlock
Key concepts
- Data catalog
- Data lineage
- OpenLineage
- Metadata ingestion
- SQL parsing
- Impact analysis
How you’ll practise
- Requirements
- Data volume
- Ingestion
- Storage and processing
- Serving and freshness
- Wrap-up
Lala, personalized to you, gives a hint when you ask and reviews your design when you are ready.
What do interviewers look for?
In any data pipeline design round.
- Clarifies sources, consumers and freshness needs
- Chooses batch, streaming or both with reasons
- Handles late, duplicate and malformed records
- Makes each stage safe to retry
- Explains storage formats and partitioning
- Plans monitoring, backfills and data quality checks
Questions people ask about this interview question
- Which design type is this question?
- It is a data pipeline question. You design a data catalog and lineage system and explain your choices the way you would in an interview.
- Is this question asked at entry level?
- It is marked Medium. Entry-level engineers can practise it, but it expects you to reason about requirements and trade-offs, not only list components.
- What should I cover first?
- Start with the data sources, the consumers and how fresh the data must be. Agree on scope with the interviewer before you design anything.
- Can I practise it for free?
- It is a premium question. Sign up and unlock it once for 10 credits; it then stays unlocked. When you finish, Lala, your personalized AI mentor, can review your design for 30 credits.
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Updated · Written by the SevyDevy team