Data Engineer – People Analytics

About the role

DoorDash is expanding its engineering presence in São Paulo and is looking for a Data Engineer to join the People Intelligence team. You will help build and scale the data infrastructure that powers people‑focused analytics, enabling better decisions around talent attraction, development, and retention.

Key responsibilities

• Architect and engineer data infrastructure for People data.
• Design and implement data‑warehouse schemas, tables, and views to create reliable datasets.
• Develop ETL pipelines using Airflow, dbt, and other orchestration tools for data profiling, cleaning, and transformation.
• Support self‑service analytics by creating secure, well‑documented data structures.
• Provide data support for People metrics such as recruiting pipelines, attrition, employee engagement, diversity, compensation, and benefits.
• Ensure data integrity and rigorously document system requirements and configurations.
• Contribute to AI‑ready data marts and data‑governance initiatives.
• Identify improvement opportunities and train peers on new processes.

Required profile

• 5+ years of experience in data engineering, business intelligence, or software engineering.
• Expertise in SQL and ability to write complex queries.
• Proficiency in Python or Java.
• Hands‑on experience with ETL orchestration tools (Airflow, Flink, Oozie, Azkaban) on AWS or GCP.
• Experience authoring Airflow DAGs and using data‑observability/monitoring frameworks.
• Familiarity with Snowflake or similar cloud data warehouses.

Required skills

• SQL
• Python
• Java
• Airflow
• dbt
• AWS
• GCP
• Snowflake
• Flink
• Oozie
• Azkaban
• Data observability tools