Staff Security Data Engineer

What you'll do

• Lead end-to-end platform architecture and implement distributed batch and streaming pipelines, infrastructure, and data models.
• Establish data governance, orchestration, testing, observability, and production recovery practices; improve platform performance, cost, and reliability.
• Lead cross-team technical decisions and mentor engineers; evaluate AI-assisted engineering and operational automation while protecting sensitive data.

What they ask for

• Production data platform or software engineering experience, typically 10 or more years, with demonstrated Staff-level scope and impact; equivalent depth and outcomes are welcome.
• Deep production expertise in Spark, Databricks, Delta Lake, and lakehouse architecture; strong Python and advanced SQL skills.
• Strong AWS experience and production Terraform experience designing, testing, and maintaining reusable modules.
• Experience with Airflow, MWAA, or equivalent orchestration, and production observability, data quality, automated testing, CI/CD, and reliable deployment and recovery practices.

Nice to have

• Security telemetry, OCSF or comparable security schemas, and data requirements for SIEM, SOAR, threat detection, or investigations.
• Unity Catalog governance, data classification and retention, regional data controls, multi-region design, or telemetry routing tools such as Cribl Stream or Vector.

Pay

$159,200 - $301,600 annually USD (base salary); $208,300 - $301,600 USD (base salary, California)

Tools

Databricks, AWS, Spark, Delta Lake, Unity Catalog, Python, SQL, Terraform

AI focus

Evaluate and introduce AI-assisted engineering and operational automation; validate outputs, protect sensitive security data, measure improvements, and support adoption. AI or recording tools are not permitted during live interviews unless invited or approved in advance as a reasonable accommodation.