Lead Data Engineer

About the role

We are seeking a Lead Data Engineer to own the data pipeline and analytical architecture for a high‑volume marketing analytics platform. You will shape the design of our S3‑backed data lake, define partitioning, file formats, schema, and near‑real‑time processing strategies.

Key responsibilities

• Design, build, and maintain scalable ETL pipelines that ingest data from internal databases and external APIs.
• Make architectural decisions on partitioning, file formats (Parquet/ORC), schema design, and OLAP‑oriented data structures.
• Define and manage DAG‑based batch workflows on Airflow, setting pipeline structure, dependencies, and triggers.
• Drive the AWS data stack (S3, Athena, EKS/Kubernetes) in partnership with DevOps.
• Review pull requests, enforce code quality, and mentor senior developers.

Required profile

• 7+ years of engineering experience with a proven record of designing and implementing large‑volume ETL pipelines.
• Hands‑on experience with OLAP‑style analytical data architecture and data lakes on object storage.
• Deep familiarity with DAG‑style workflow orchestration (Airflow or comparable tools).
• Ability to lead a team of senior developers and align with engineering best practices.

Required skills

• ETL pipeline design and implementation
• AWS services: S3, Athena, EKS, Kubernetes
• Airflow (or Dagster, Prefect, Luigi, Step Functions)
• Data lake concepts, partitioning, Parquet, ORC
• OLAP technologies: Athena, Trino/Presto, BigQuery, Snowflake, Spark SQL, ClickHouse