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Services · Data engineering

Make your data ready for the models you want to ship.

We build the lakehouse, the pipelines, the feature store, and the lineage layer that turns scattered source systems into governed inputs your analysts and your models can both rely on.

What you get

Three concrete deliverables.

First domain in 8 weeks

Lakehouse and ingest plane

Bronze/silver/gold tables on Delta or Iceberg, CDC ingestion from your source systems, and SLAs on freshness wired to alerts your team owns.

Stood up with model handoff

Feature store and model inputs

Reusable features with point-in-time correctness, offline-to-online parity, and the governance layer your model risk team needs.

On from week one

Observability and lineage

OpenLineage or equivalent across every pipeline, alerting on freshness and schema drift, and dashboards your engineers actually use.

How we work

From kickoff to production.

012 weeks

Source and use-case audit

Inventory source systems, downstream consumers, and the use cases data has to serve. Identify the narrowest first domain to land end to end.

023 weeks

Platform and contract design

Pick the lakehouse stack, design data contracts between producers and consumers, and write the governance policy you will live by.

036 weeks

First domain in production

Build the ingest, transformation, and serving for the first domain end to end. Freshness, lineage, and alerting from day one.

04Continuous

Domain expansion and ownership transfer

Add domains on a steady cadence, paired with knowledge transfer so your data engineers own each domain at the end of its build.

The stack we build on.

Cloud-agnostic. We meet you where your tenant lives.

Databricks / SnowflakeDelta Lake / Apache IcebergdbtAirflow / DagsterDebezium CDCOpenLineageFeature stores (Feast / Tecton)Kubernetes

Outcome metrics

85%
Pipeline freshness on SLA

Rolling 30-day, post-stabilization

6x
Reduction in ad-hoc data tickets

Versus pre-engagement baseline

<2hr
Detect-to-alert on schema drift

Median, across monitored pipelines

From the field

One we shipped.

Commercial lender · risk

Replaced a nightly batch with a CDC-backed lakehouse so the risk team queries against data that is minutes old, not a day old. First domain live in seven weeks.

12min

End-to-end ingest latency

Down from 18 hours

Read the case study

FAQ

Questions buyers ask first.

Lakehouse or warehouse — what do you recommend?
Both, often together. Lakehouse for the raw and transformed analytical plane, a warehouse where SQL-first reporting needs the indexing and concurrency. We pick on workload shape, not on vendor preference.
How do you handle data contracts between teams?
We write them as code in the producer's repo, validate them in CI, and break the build when a schema change would silently break a consumer. Producers own the contract, consumers depend on it, breakage is loud.
Do you do governance and lineage, or just the pipes?
Both. Lineage is wired from the first domain on day one — not bolted on later — and the governance policy (PII handling, retention, masking) ships as runnable policy, not a PDF.
What does a feature store actually buy us?
Point-in-time correctness for training, offline-to-online parity for inference, and a reusable layer so the same feature does not get reimplemented by three teams. We ship one when ML use cases need it, not as a vanity install.
Who owns the platform when you leave?
Your data engineers. We pair on the first domain, take a back seat by the third, and transfer the platform with runbooks, governance, and a written upgrade path. Default is full handoff.

Related services

What buyers usually pair with this.

AI engineering

Production model serving on top of the feature store and lineage layer your data team owns.

See the service

RAG and knowledge systems

Retrieval over the same governed lakehouse instead of standing up a parallel data plane just for AI.

See the service

Cloud modernization

Lift the source systems and the data platform together so the lakehouse does not inherit legacy debt.

See the service

Ready to scope this?

Thirty minutes with a principal. We will walk through your constraints and what a 30- to 90-day pilot would actually look like.