Marketing Data Stack Build
A modern data stack built for how marketing teams actually work.
Who it’s for
You’ve outgrown spreadsheets and single-tool dashboards. You need a proper stack — ingestion, warehouse, modeling, reporting — that your marketing team can rely on and your CFO can sign off on. You don’t have the in-house people to build it.
What you get
- Ingestion layer (dlt, Fivetran, or Airbyte — picked for fit) pulling from your ad platforms, CRM, and relevant sources
- BigQuery or Snowflake warehouse, set up with environments, IAM, and cost controls
- dbt project structured for your business — staging, intermediate, marts — with tests and documentation
- Dashboards in Looker Studio, Metabase, or Lightdash (your preference)
- CI/CD, documentation, and a handoff your team can run with
How it works
- Discovery call
Free.
- Scoping
1 week. I audit your current setup and sources, scope the build, deliver a fixed quote.
- Setup
Weeks 1–2. Infrastructure, ingestion, warehouse.
- Modeling
Weeks 3–6. dbt project, business logic, testing.
- Reporting
Weeks 6–8. Dashboards and self-serve layer.
- Handoff
Weeks 8–10. Documentation, team training, 30-day support.
Who it’s not for
- Companies with fewer than 3 marketing data sources — this is overkill
- Teams with existing data engineers who just need a pair of hands — consider the fractional engagement instead
Frequently asked
Warehouse: BigQuery or Snowflake?
BigQuery for most cases — cheaper to start, Google-native. Snowflake if your team prefers it or needs multi-cloud.
Will I be locked into you after the build?
No. I build stacks teams can own. Documentation and training are part of the deliverable. If you want ongoing support, the fractional engagement is there for that.
What if something’s broken post-launch?
30 days of support are included. After that, fractional or retainer options.