Data Engineering Manager - Scale, Leadership, Hybrid

DoorDash, Inc.; San Francisco (CA); Hybrid; USD 210,000 - 320,000; Full time

Job summary

DoorDash is seeking a Data Engineering Manager to guide enterprise-scale data solutions and act as a technical expert in data architecture. You will empower a community of engineers, data scientists, and partners, fostering an engineering culture of excellence in a dynamic, hybrid work environment.

Located in San Francisco, Sunnyvale, or Seattle, this role focuses on data platforms, pipelines, and governance to support reporting, analytics, and product decisions at scale.

Qualifications

• BS, MS, or PhD in Computer Science or equivalent.
• 10+ years in data engineering or related domain.
• 2+ years hands-on management experience.
• Experience hiring and growing teams.
• Strong communication and leadership in fast-moving environments.
• Hands-on with SQL and Python.
• Proficient with large-scale ETL and data architectures.
• Familiar with cloud data platforms (AWS/GCP) and big data tools.

Responsibilities

• Lead and grow a data engineering team delivering enterprise-scale data solutions.
• Set technical vision for data architecture and enable data scientists and engineers.
• Drive reliable, scalable data pipelines and governance across systems.
• Collaborate with stakeholders to align data strategy with business goals.
• Mentor engineers, manage performance and ensure engineering excellence.

Tools

Snowflake

Redshift

AWS

GCP

Hadoop

Spark

Flink

Airflow

Delta Lake

Iceberg

CockroachDB

PostgreSQL

Job description

DoorDash is seeking a Data Engineering Manager to guide enterprise-scale data solutions and act as a technical expert in data architecture. You will empower a community of engineers, data scientists, and partners, fostering an engineering culture of excellence in a dynamic, hybrid work environment.

Located in San Francisco, Sunnyvale, or Seattle, this role focuses on data platforms, pipelines, and governance to support reporting, analytics, and product decisions at scale.