Staff Data Engineer

Role overview

Set technical direction for a data engineering platform that moves information from source systems into reliable, decision-ready data. This senior individual-contributor role owns architecture and standards across ingestion, orchestration, governance, and delivery, and takes on complex problems that require judgment beyond established runbooks.

Responsibilities

- Architect ingestion pipelines, orchestration, and data delivery systems; write design guidance that other engineers can implement. - Establish reusable standards for pipelines, Airflow workflows, testing, monitoring, and data catalog registration. - Lead investigation of difficult integrity, performance, and reliability issues, turning recurring failures into systemic fixes, automation, or runbooks. - Define reliability goals and alerting practices, improve on-call health, and reduce operational toil. - Set data security and governance practices, including access controls, sensitive-data masking, classification, and lineage. - Design integrations for reverse ETL and downstream delivery, specifying service expectations and failure handling. - Guide platform choices and cost planning across data and cloud services; review designs and high-risk changes for failure modes and downstream impact. - Work with analytics, product, data science, and business partners; mentor engineers and help shape technical direction.

Requirements

- At least eight years of software or data engineering experience, including ownership of production data platforms at scale. - Track record delivering large, cross-team data systems from unclear requirements through production operation. - Advanced Python and SQL skills, with deep ETL/ELT experience for complex, high-volume transformations. - Deep experience with Airflow or Managed Workflows for Apache Airflow, including large-scale workflow design and operations. - Strong command of pipeline reliability concepts such as idempotency, backfills, schema evolution, late-arriving data, quality checks, and recovery. - Hands-on experience with several of Snowflake, Databricks, AWS, dbt, Tableau, MongoDB, and PostgreSQL. - Experience building governance capabilities and reusable frameworks, plus strong testing, CI/CD, and code review practices. - Ability to mentor, build alignment across teams, and communicate decisions through design documents, trade-off analysis, and incident reports.

Nice to have

- Experience with reverse ETL, streaming systems such as Kafka, observability tools, cloud cost governance, or major platform migrations. - Background in gaming, betting, e-commerce, or another regulated sector.

Benefits and work setup

- Some interview and onboarding activities may be in person, depending on the role and location. The listed US base salary range is $180,500–$237,500, subject to geographic compensation zones.