Senior Data Engineer - Digital Marketing

Role overview

Build and operate data pipelines that support a media measurement and planning product. The work spans large-scale data transformations, production reliability, and performance and cost improvements, with close collaboration across engineering and business teams.

Responsibilities

- Design, build, and maintain scalable ETL pipelines for large data volumes. - Use PySpark and Databricks to implement complex transformations and workflows. - Tune pipelines for performance, scalability, and cloud compute efficiency. - Diagnose processing failures and bottlenecks, then prevent recurring issues. - Work with technical and business partners to turn requirements into data solutions. - Apply practices that support data quality, governance, and reliable operations.

Requirements

- 5–7 years of hands-on data engineering experience delivering production systems. - Strong PySpark skills and substantial experience with Databricks. - Advanced knowledge of Databricks AutoLoader and Python. - Deep understanding of end-to-end ETL, complex transformations, and pipeline optimization. - Experience improving performance and controlling compute costs. - Strong problem-solving skills and clear communication with technical and non-technical audiences.

Benefits and work setup

- Fully remote work, with location flexibility. - Paid time off and autonomy over work scheduling. - Compensation is paid in USD; the source does not specify an amount.