The role involves designing, building, and maintaining ETL pipelines for data ingestion, transformation, and delivery. The individual will automate and maintain report generation processes while building scalable data transformations. Responsibilities include applying cloud best practices for data storage, performance, and cost management. The engineer will own production pipelines, monitor performance, and implement continuous improvements. Additionally, the role requires troubleshooting data issues, writing maintainable code, and participating in code reviews. The position involves partnering with analytics, engineering, and product teams to deliver data solutions for financial use cases.

Candidates must possess a degree in Computer Science, Information Science, or a related quantitative field. A minimum of five years of experience in building and maintaining ETL pipelines using Python is required. Applicants need strong experience with data warehouses, analytics platforms, and workflow orchestration tools. Proficiency in cloud platforms, data services, and transformation frameworks is necessary, along with an understanding of CI/CD and DevOps practices.