Engineering Manager, Data

DoorDash DoorDash · Consumer · Seattle, WA · 318 Data

DoorDash is seeking an Engineering Manager for their Data team to lead the development of enterprise-scale data solutions. This role involves managing a team of data engineers, driving technical vision, improving data architecture, and ensuring reliability and quality. The ideal candidate will have extensive experience in data engineering, management, and big data technologies.

What you'd actually do

  1. You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams
  2. You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability
  3. You strive for continuous improvement of data architecture and development process
  4. You think of quick wins while planning for long term strategy and engineering excellence. You are excited about breaking down large systems into easy to use data assets and reusable components
  5. You are excited about cross collaboration with stakeholders, external partners and peer data leaders

Skills

Required

  • B.S., M.S., or PhD. in Computer Science or equivalent
  • 10+ years of experience working in data engineering or a related domain
  • 2+ years of hands-on management experience
  • Experience hiring and growing teams
  • Exceptional communication and leadership skills, with a proven ability to operate in a fast moving environment
  • Experienced with performance management, coaching, mentoring and growing teams
  • Hands-on approach to closing gaps in data infrastructure and technical execution, able to code in SQL and Python
  • Prior experience with Snowflake/Redshift, AWS/GCP, Hadoop/Spark/Big data, Lambda/KAPPA architectures, Flink/Airflow
  • Prior experience with large scale batch/real time ETL orchestration
  • Prior experience in Systems Engineering - you've built meaningful big data processing systems at scale, and experience with big data compute engines such as Apache Spark and Apache Flink
  • Familiarity with Datalake solutions such as Delta Lake, Apache Iceberg
  • Familiarity with a cloud based environment such as AWS

Nice to have

  • Building systems directly powering online applications
  • Exposure to various databases such as CockroachDB, Cassandra, and PostgreSQL

What the JD emphasized

  • reliability and quality as must have