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.

Bachelor’s degree in Computer Science, Engineering, Mathematics, or other technical discipline (proven professional experience will be considered in lieu of a technical degree).
2+ years of recent advanced Snowflake development experience.
Experience manipulating healthcare data In-depth knowledge of Amazon Web Services (AWS) and Platform as a Service (PAAS).
Demonstrable experience with Snowflake utilities including SnowSQL & Snowflake Javascript.
Ability to analyze all aspects of the Snowflake Query Engine to improve bottlenecks that may exist.
Ability to automate data ingestion from Amazon S3, FTP, and other technologies.
Experience with scripting languages. Extensive Python experience.
Working knowledge of Bitbucket and Git.
Experience managing and loading data in AWS RDS (MySQL/MariaDb).
Ability to optimize MySQL query execution plans for robust performance.
Strong analytical skills and ability to rapidly switch contexts.
Excellent communication and problem-solving skills.
Passion to uncover and improve processes that are inefficient or sub-optimal.
Track record of implementing creative solutions to complex problems.
Experience working in a nimble, fast-paced, growth start-up environment.

Senior Data Engineer

Key skills