Senior Data Engineer: Scale Data Lakes & Pipelines

DoorDash ANZ; San Francisco (CA); Hybrid; USD 131,000 - 285,000; Full time

Benefits offered by this job

401(k) matching

Paid parental leave

Wellness benefits

Commuter benefits match

Paid time off

Job summary

DoorDash is seeking a Senior Data Engineer to scale data infrastructure, automation, and tools. This hybrid role requires proximity to Sunnyvale, San Francisco, or Seattle and focuses on building data lake/warehouse pipelines and ensuring data quality.

The role emphasizes collaboration with stakeholders, engineering and product teams, and onboarding new engineers to strengthen the data platform for reporting, analytics and financial data workflows.

Qualifications

• 5+ years of professional data engineering experience.
• 3+ years in data engineering, BI, or similar roles.
• Proficiency in Python/Java.
• 3+ years with ETL orchestration tools (Airflow, Flink, Oozie, Azkaban) using AWS/GCP.
• Expert in SQL, database fundamentals, and distributed computing.

Responsibilities

• Understand data requirements with business partners and stakeholders.
• Collaborate with engineers and product teams to collect data.
• Design, develop and implement large-scale data models and pipelines for data lake and data warehouse.
• Develop data quality checks, QA, and monitoring routines.
• Improve reliability and scalability of ETL processes.
• Manage data product portfolio ensuring high-quality data.

Skills

Professional data engineering

Python/Java

SQL

Data modeling

Analytics collaboration

Tools

Airflow

Flink

Oozie

Azkaban

Spark

Hive

Presto

Kafka

Snowflake

Redshift

PostgreSQL

Job description

DoorDash is seeking a Senior Data Engineer to scale data infrastructure, automation, and tools. This hybrid role requires proximity to Sunnyvale, San Francisco, or Seattle and focuses on building data lake/warehouse pipelines and ensuring data quality.

The role emphasizes collaboration with stakeholders, engineering and product teams, and onboarding new engineers to strengthen the data platform for reporting, analytics and financial data workflows.