About the role

Data Engineer owning infrastructure that turns raw events from mobile users into trustworthy data. Building scalable data architecture and collaborating with cross-functional teams for data management.

Responsibilities

Own the infrastructure that turns raw events from millions of mobile users into trustworthy data the business runs on.
Design and scale the pipelines, warehouses, and tooling.
Work side-by-side with analytics, product, and growth teams.
Design, build, and maintain scalable data architecture.
Own ingestion, transformation, storage, and modelling.
Write clean, efficient Python to power reliable pipelines.
Lead our dbt project on BigQuery.
Partner with analytics to ship Metabase dashboards.
Set the bar for what 'trustworthy data' means here.

5+ years of hands-on data engineering experience (or a closely related role with heavy pipeline and infrastructure work).
3+ years with a cloud data warehouse - BigQuery preferred, Snowflake or Redshift also fine.
2+ years of production dbt experience: dimensional and incremental models, custom macros, tests that catch real problems, and reusable packages.
Strong Python for data work - 3+ years of writing pipelines, scripts, and internal tooling that other people rely on.
3+ years with orchestration tools - Airflow, Dagster, or Prefect.
Real experience building and maintaining BI dashboards and the infrastructure behind them.
Clear, concise communication. You document what you build, explain trade-offs to non-technical people, and surface blockers early.
Strong sense of ownership and the ability to run independently in a fast-paced remote environment.