The role involves designing and delivering scalable ETL solutions to support enterprise analytics and financial or insurance data platforms. The individual will build and optimize data pipelines to process large volumes of structured and semistructured data. Responsibilities include implementing performance tuning, partitioning, and monitoring to ensure reliability. The position requires integrating pipelines with various cloud storage and analytics services while maintaining secure data handling practices. The professional will collaborate with architects and product owners to translate business requirements into functional data solutions. Additionally, the role entails supporting production workloads and adhering to software engineering best practices such as CI/CD and documentation.

The role requires a bachelor's degree, with a master's degree preferred. Candidates must possess strong hands-on experience with Python in production environments and a proven background in ETL and data pipeline development, preferably using Spark. Proficiency in AWS data services such as Glue, S3, Athena, and CloudWatch is necessary. Furthermore, the position requires solid SQL and data modeling skills, along with experience working in agile environments.