Typical work
Source ingestion, orchestration, dbt models, warehouse tuning, monitoring, backfills, and incident response.
Fractional data team
Fractional data engineer for pipelines, warehouses, and production data reliability
A senior data engineering capacity layer for teams that need real infrastructure work before they can hire, onboard, and manage a full-time data engineer.
Inspectable delivery artifact
A buyer should see the operating evidence, not only read the promise.
This service is evaluated through source contracts, quality checks, owners, failure states, and handover evidence. The preview shows the kind of artifact that belongs in the delivery packet.
Fractional data engineer for pipelines, warehouses, and production data reliability
Sample acceptance matrix
raw.orders
Check
loaded_at < 10m
State
pass
Owner
Data eng
stg_payments
Check
unique payment_id
State
pass
Owner
Finance
mart_revenue
Check
reconciles to Stripe
State
review
Owner
RevOps
| Artifact | Check | State | Owner |
|---|---|---|---|
| raw.orders | loaded_at < 10m | pass | Data eng |
| stg_payments | unique payment_id | pass | Finance |
| mart_revenue | reconciles to Stripe | review | RevOps |
Role scope
A fractional data engineer owns implementation work in your data stack: connectors, pipelines, transformations, quality tests, warehouse objects, and reliability improvements. The role is not a generic analyst or dashboard-only support function.
We operate through written tickets, source-controlled code, deployment notes, and runbooks so the work remains transferable.
- Pipeline build
- Warehouse models
- dbt and SQL work
- Backfills
- Data quality tests
- Operational monitoring
When this fits
This is for teams that have recurring data engineering work but cannot yet justify or recruit the full-time role. It also fits teams whose engineers are overloaded with product work and need data infrastructure support.
- Pre-hire data team
- Founder-led reporting
- Messy warehouse recovery
- Connector backlog
- Dashboard reliability issues
- Data platform maintenance
Engagement model
We scope retained capacity around outcomes: pipeline backlog, reliability targets, metric delivery, or migration phases. Every month ends with a written summary of shipped work, open risks, and next priorities.
- Monthly capacity plan
- Sprint board
- Code handover
- Reliability report
- Risk register
- Next-month roadmap
Working surface
Map the first reliable data path.
Bring the source exports, dashboards, and decisions that currently create friction. We return a scoped pilot path with owners, evidence, and handover expectations.