Data Engineer, People Analytics

Responsibilities

• Architect and engineer data infrastructure for People data
• Design and implement data warehouse schemas, tables, and views
• Develop ETL pipelines using Airflow and dbt for data profiling, cleaning, and transformation
• Support self-service analytics projects by creating secure data structures
• Provide underlying data support for all People metrics including recruiting, attrition, and diversity
• Ensure data integrity and rigorously document system requirements
• Contribute to building AI-ready data marts
• Help build data governance with a single source of truth

Requirements

• 5+ years of industry experience in data engineering, business intelligence, or software engineering
• Expert SQL skills and experience writing complex queries
• Proficiency in programming languages such as Python or Java
• Experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie, or Azkaban using AWS/GCP
• Proficiency authoring Airflow DAGs
• Experience with data observability and monitoring frameworks
• Experience working with Snowflake, Redshift, PostgreSQL, and/or other DBMS platforms

Preferred Qualifications

• dbt (data build tool) as a project admin and authoring models
• Experience with monitoring services like Splunk
• Experience with observability services like Monte Carlo

About the Company

DoorDash is building the world’s most reliable on-demand logistics platform. We are a technology and logistics company that empowers local economies, moving from food delivery to a platform for all goods.