Senior Data Engineer - PySpark / ETL

About this kind of role

What a Senior Data Engineer - PySpark / ETL usually does. The employer's own details are in the listing.

Typically does: Designs, builds, and maintains data pipelines to transform and load data from various sources into data warehouses or data lakes. Develops and implements Extract, Transform, Load (ETL) processes to ensure data quality and consistency. Optimizes data infrastructure for performance and scalability, often working with large datasets. Collaborates with data scientists, analysts, and other engineers to meet data-related needs.

Tools and skills: Proficiency in Python, Spark (PySpark), SQL, and experience with cloud platforms like AWS, Azure, or Google Cloud, along with ETL tools and data warehousing concepts.

Good fit for: Individuals with strong analytical and problem-solving skills who enjoy working with data and building robust, scalable systems are often successful in this role.