• Champion a comprehensive data vision and operating principles that improve data quality, consistency, accessibility, decision making, use, and stewardship. • Manage data pipeline by developing processes for data input, transformation, and storage. • Act as an interface between the Data Science team and Application Developers. • Architect and implement front-end (application layer) and back-end (ETL layer) database technologies in a highly customized data environment. • Develop automated processes for moving data between systems. • Implement ETL processes that transform source data into functional data stores consumed by front-end applications. • Scale data pipeline by utilizing the most efficient tools and technologies.