Data Engineer

Responsibilities

• Ship and operate production pipelines across batch, streaming, and reporting stacks, from requirements to monitoring
• Design storage and compute for petabyte-scale datasets using Iceberg, Spark, DuckDB, and Trino
• Cut cost and latency on specific pipelines and queries, with quantified, instrumented impact
• Own the data contract for the ClickHouse and Cube reporting stack behind the Clear UI
• Build alerts, SLOs, and runbooks so fewer incidents reach users
• Lead incident response and carry on-call across production systems
• Influence upstream producers on schemas, semantics, and SLAs for bid, win, and impression events
• Build tooling, conventions, and data contracts that make the whole team faster

Requirements

• 5+ years building and operating production data platforms at real volume, not analytics or BI‑adjacent work.
• Deep lakehouse experience across storage (Iceberg, Delta, or Hudi) and compute (Spark, DuckDB, or Trino)
• Production experience with a modern orchestrator (Dagster, Airflow, or Prefect) plus dbt or an equivalent transformation framework
• A proven track record of handling large volumes of data under time and cost constraints.
• Operational ownership: on-call, incident response, alerts and runbooks you actually wrote
• Cross‑functional communication: you adapt detail to the audience and push back on stakeholders constructively