Data Quality & Governance
dbt tests, lineage, and a catalog so every metric has an owner and a definition.
dbt tests, Great Expectations, column lineage, and a searchable catalog — so every metric has an owner, SLA, and shared definition.
Problems I solve
- Different teams reporting different numbers
- Silent data breakage no one catches
- No lineage — nobody knows what depends on what
- New hires can't find the right table
What you get
- dbt tests + Great Expectations suites
- Column-level lineage
- Data catalog (DataHub / OpenMetadata)
- SLAs, owners, and freshness alerts
Use cases
Bootstrapping data tests
Test coverage across critical marts + freshness SLAs.
Data catalog rollout
Cataloged, owned, and documented tables searchable by all teams.
Lineage & impact analysis
See what breaks downstream before shipping a schema change.
Compliance-ready governance
PII tagging, access controls, and audit-ready lineage.
Examples I've shipped
SaaS dbt test coverage
Outcome — Data incidents down 80% in one quarter.
DataHub rollout
Outcome — Cataloged 900 tables, cut 'where is X?' Slack pings 90%.
How I work
- 1
Audit
Inventory tables, current tests, and pain points.
- 2
Test rollout
Critical-path dbt + GX tests with CI gates.
- 3
Catalog
Deploy catalog with owners and freshness SLAs.
- 4
Enable
Team training + runbook for on-call.
Deliverables
- Test suite
- Data catalog
- Lineage graphs
- Ownership + SLA doc
Benefits
- Trust in the numbers
- Data incidents caught early
- New hires productive faster
Frequently asked questions
DataHub or OpenMetadata?+
Both are strong — DataHub for scale + LinkedIn heritage, OpenMetadata for ease of setup. I pick based on your team size and infra.