Data Engineering Specialist: Scale ETL & Data Pipelines

DoorDash, Inc.; San Francisco, Sunnyvale, Seattle (CA, CA, WA); On-site; USD 118,000 - 173,000; Full time

Benefits offered by this job

401(k) plan with employer matching

16 weeks paid parental leave

wellness benefits

commuter benefits match

paid time off and sick leave

Job summary

DoorDash is seeking a Software Engineer to scale data infrastructure, automation, and tools for our data lake and warehouse. You will partner with business units to collect data, build high-performance pipelines, and ensure data quality and reliability.

You will work with Python/Java, SQL, and modern data tools, collaborating across engineering, product, and analytics teams to deliver scalable data solutions in a fast-paced environment.

Qualifications

• 3+ years of data engineering or BI experience.
• Proficiency in Python/Java and SQL.
• Experience with ETL orchestration tools (Airflow, Flink, Oozie, Azkaban).
• Knowledge of data warehouses (Snowflake, Redshift) and distributed systems (Spark, Hive).
• Experience with BI/reporting tools (Tableau, Superset, Looker).
• Excellent communication with technical and non-technical teams.

Responsibilities

• Understand data requirements with business partners.
• Collaborate with eng, product and 3rd parties to collect data.
• Design and implement large-scale data models and pipelines for Data Lake/Warehouse.
• Develop data quality checks, QA, and monitoring routines.
• Improve reliability and scalability of ETL processes.
• Manage data products and onboard new engineers.

Skills

Python/Java

Airflow/Flink/Oozie

SQL

Spark/Hive/Druid/Presto

Snowflake/Redshift

Tableau/Superset/Looker

Data modeling

Tools

Git

Job description

DoorDash is seeking a Software Engineer to scale data infrastructure, automation, and tools for our data lake and warehouse. You will partner with business units to collect data, build high-performance pipelines, and ensure data quality and reliability.

You will work with Python/Java, SQL, and modern data tools, collaborating across engineering, product, and analytics teams to deliver scalable data solutions in a fast-paced environment.