Staff Data Engineer: Lead Data Pipelines & Platforms

DoorDash USA; San Francisco, Sunnyvale, Seattle (CA, CA, WA); Sur place; USD 131 000 - 285 000; Plein temps

Résumé du poste

DoorDash is seeking a Staff Software Engineer, Data Engineering to act as a technical lead for data reliability, infrastructure, and automation. You will architect and scale high-volume data systems, pipelines, and tools to meet growing business needs across multiple product areas.

You will own critical data systems, set best practices for data infra, and mentor other engineers while managing a portfolio of data products delivering trustworthy data.

Qualifications

• 8+ years of hands-on engineering and leadership experience.
• 6+ years in data platform and data engineering.
• Proficiency with Python, Kotlin, or Scala in full lifecycle development.
• 4+ years in ETL orchestration and Airflow or similar tools.
• Expertise in SQL, data reliability, and distributed data ecosystems.
• Excellent communication and ability to work with cross-functional teams.

Responsabilités

• Own critical data systems supporting multiple products/teams.
• Develop and enforce best practices for data infrastructure and automation.
• Design and scale data models and pipelines for Data Lake/Warehouse.
• Improve reliability and scalability of ingestion, processing, and reporting.
• Manage a portfolio of data products delivering high-quality data.
• Onboard and support other engineers joining the team.

Connaissances

Python/Kotlin/Scala

AI coding tools

Data modeling

Distributed computing

Communication skills

Self-starter

Outils

Airflow

Spark

Presto

Kaa/Flink/Spark Streaming

Description du poste

DoorDash is seeking a Staff Software Engineer, Data Engineering to act as a technical lead for data reliability, infrastructure, and automation. You will architect and scale high-volume data systems, pipelines, and tools to meet growing business needs across multiple product areas.

You will own critical data systems, set best practices for data infra, and mentor other engineers while managing a portfolio of data products delivering trustworthy data.