This position is no longer accepting applications
Closed on June 22, 2026.
Senior Software Engineer, Data Engineering
Senior
Big Data
Data Engineer
Data Integration
Data Lake
Data Quality
Data Warehouse
Engineer
Engineering
ETL
Spark
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Job Description
Senior Data Engineer role at DoorDash focusing on scaling data infrastructure, automation, and pipelines, with a hybrid setup near San Francisco, Sunnyvale, or Seattle.
Responsibilities
- Collaborate with business partners and stakeholders to capture data needs and requirements
- Coordinate with engineering, product teams, and external partners to gather necessary data
- Architect and build scalable, high volume data models and pipelines for Data Lake and Data Warehouse environments
- Create and enforce data quality checks, perform QA, and implement monitoring routines
- Enhance the reliability and scalability of ETL processes
- Oversee a portfolio of data products delivering accurate and trustworthy data
- Onboard and mentor new engineers joining the team
Requirements
- 5+ years of professional experience
- 3+ years in data engineering, business intelligence, or a similar role
- Proficiency in programming languages such as Python or Java
- 3+ years using ETL orchestration and workflow management tools such as Airflow, Flink, Oozie, and Azkaban on AWS or GCP
- Strong foundation in database fundamentals, SQL, and distributed computing
- 3+ years in distributed data ecosystems (Spark, Hive, Druid, Presto) and streaming technologies like Kafka or Flink
- Experience with Snowflake, Redshift, PostgreSQL or other DBMS platforms
- Excellent communication skills and experience collaborating with technical and non technical teams
- Knowledge of reporting tools such as Tableau, Superset, and Looker
- Comfortable in a fast paced environment, self starter and self organizing
- Ability to think strategically and analyze market and consumer information
- Must be located near one of the engineering hubs listed above
Technologies
- Python
- Java
- Airflow
- Flink
- Oozie
- Azkaban
- AWS
- GCP
- Spark
- Hive
- Druid
- Presto
- Kafka
- Snowflake
- Redshift
- PostgreSQL
- Tableau
- Superset
- Looker
Benefits
- Premium healthcare
- Wellness expense reimbursement
- Paid parental leave