Senior Software Engineer, Data Engineering

DoorDash DoorDash · Consumer · San Francisco, CA · 318 Data

Senior Data Engineer role focused on building and scaling data infrastructure, pipelines, and data models for a data-driven company. Responsibilities include designing, developing, and implementing large-scale data solutions, ensuring data quality, and improving ETL processes. Requires strong experience in data engineering tools, SQL, distributed computing, and cloud platforms.

What you'd actually do

  1. Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse
  2. Develop and implement data quality checks, conduct QA and implement monitoring routines
  3. Improve the reliability and scalability of our ETL processes
  4. Manage a portfolio of data products that deliver high-quality, trustworthy data
  5. Help onboard and support other engineers as they join the team

Skills

Required

  • Python/Java
  • ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP
  • Database fundamentals, SQL and distributed computing
  • Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink.
  • Snowflake, Redshift, PostgreSQL and/or other DBMS platforms
  • reporting tools such as Tableau, Superset and Looker

Nice to have

  • Excellent communication skills and experience working with technical and non-technical teams
  • Comfortable working in fast paced environment, self starter and self organizing
  • Ability to think strategically, analyze and interpret market and consumer information

What the JD emphasized

  • 5+ years of professional experience
  • 3+ years experience working in data engineering, business intelligence, or a similar role
  • 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP
  • 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink.