Senior Data Engineer: Build Scalable Data Pipelines

DoorDash, Inc.; Sunnyvale (CA); Híbrido; USD 144.000 - 212.000; Jornada completa

Descripción de la vacante

DoorDash is seeking a Senior Data Engineer to scale data infrastructure, automation, and tools. This hybrid role requires you to be located in Sunnyvale, San Francisco, or Seattle and to work with cross-functional teams to deliver high-quality data products.

You will design and optimize pipelines for a Data Lake and Data Warehouse, implement data quality checks, and enhance ETL reliability. Strong collaboration and communication across technical and non-technical teams are essential.

Formación

• 5+ years of professional experience in data roles.
• 3+ years in data engineering, BI, or similar.
• Proficiency in Python/Java.
• 3+ years with ETL orchestration tools (Airflow, Flink, Oozie, Azkaban) on AWS/GCP.
• Expert in SQL, databases, and distributed computing.
• 3+ years with Spark, Hive, Druid, Presto; streaming with Kafka/Flink.
• Experience with Snowflake/Redshift/PostgreSQL.
• Knowledge of Tableau, Superset, Looker.

Responsabilidades

• Understand data requirements with business partners.
• Collaborate with engineering, 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.
• Improve reliability and scalability of ETL processes.
• Manage data product portfolio delivering high-quality data.
• Onboard and support other engineers joining the team.

Conocimientos

Data engineering

SQL

Distributed computing

Python/Java

Kafka/Flink

Spark/Hive/Druid/Presto

Snowflake/Redshift/PostgreSQL

Tableau/Superset/Looker

Herramientas

Airflow

Flink

Oozie

Azkaban

AWS/GCP

Descripción del empleo

DoorDash is seeking a Senior Data Engineer to scale data infrastructure, automation, and tools. This hybrid role requires you to be located in Sunnyvale, San Francisco, or Seattle and to work with cross-functional teams to deliver high-quality data products.

You will design and optimize pipelines for a Data Lake and Data Warehouse, implement data quality checks, and enhance ETL reliability. Strong collaboration and communication across technical and non-technical teams are essential.