Senior Data Platform Engineer.
Postgres to Iceberg to dbt to metric layer. You think reverse-ETL is underrated and feature stores are oversold.
About the role
You will build and improve data platforms that engineering and operations teams can trust.
The role covers ingestion, transformation, warehouse and lakehouse design, dashboards, and data reliability.
What you'll do
- Design data pipelines, schemas, and contracts that are understandable and operable.
- Build transformations and dashboards that support engineering and business decisions.
- Improve data quality, observability, lineage, and incident response for analytics systems.
- Connect data work to platform reliability instead of treating it as a separate universe.
Who you are
- You have built or operated production data pipelines.
- You understand SQL, warehouses or lakehouses, orchestration, and data quality checks.
- You can work across application, infrastructure, and analytics boundaries.
- You care about making data systems boring, documented, and trusted.
Bonus, not required
- Iceberg, dbt, Airflow, Dagster, or Kafka experience.
- Postgres and analytical database depth.
- Experience with regulated or customer-facing data systems.
Interview process
- Application, resume, GitHub, and a short paragraph.
- Engineering chat, 60 minutes with a senior engineer. No whiteboard.
- Take-home, paid, scoped work on a real engineering problem.
- Team day, focused conversations around design, security, and collaboration.
- Offer, written clearly and discussed directly.
Compensation & benefits
Competitive senior-engineer compensation, full-time, remote-first, US. We discuss specifics early in the process so nobody is left guessing.
- Medical, dental, and vision benefits
- Flexible paid time away from work
- Home-office and learning support
- Time for writing, open engineering, and internal platform improvement