AWS Data Engineer

Data Engineer -

• Should have 10+ Yrs of experience as Data Engineer.
• Build ETL pipelines using technologies such as Python and Spark
• Implement new ETL pipelines on top of a variety of architectures (e.g. file-based, streaming)
• Optimally store large datasets using a variety of file formats (e.g. Parquet, JSON) and table types (e.g. Iceberg, Hive)
• Work with Data Analysts and Data Scientists to understand and make available the data that is important for their analysis
• Work with our Data Platform, Architecture, and Governance sibling teams to make data scalable, consumable, and discoverable
• Leverage Cloud-based technologies (mostly AWS, some GCP) to build and deploy data pipelines

We’re looking for someone with:

• Strong knowledge of Oracle / Mongo DB.
• 2+ years of building ETL pipelines for a Data Lake/Warehouse
• 2+ years Python experience
• 2+ years Spark experience
• Hive, Iceberg, Glue, or other technologies that expose big data as tables
• Familiarity with different big data file types such as Parquet, Avro, and JSON
• Background in building data platforms in the Cloud (e.g. AWS, GCP, Azure)
• Experience building RAG-based tools is a plus