Data Engineer III

Myriad Genetics•Salt Lake City, UT

22h

About The Position

Lead the design, development, and maintenance of ETL processes using Snowflake and AWS Cloud Services. Extract structured and semi-structured commercial datasets from upstream Oracle source systems into Snowflake cloud data warehouses, and use Fivetran to support data extraction, transformation, and loading. Improve business data pipelines for efficiency, performance, and scalability. Use BigQuery for complex data transformations supporting marketing teams and create dashboards using Looker. Develop custom frameworks using SFTP and APIs to handle data in CSV, JSON, and relational database formats. Maintain data codebase integrity, version-control pipelines, and support software deployment using GitHub. Build frameworks for data transformations across structured and unstructured formats, including automated scheduling and monitoring. Generate and troubleshoot advanced code using SQL and Python, implement automated data quality checks and validation, collaborate with commercial product managers on reliable data delivery, document ETL processes and data models, and keep current with emerging data engineering technologies and trends. Telecommute is possible.

Requirements

Master’s degree in Computer Science.
At least 2 years of experience in the job offered.
Proficiency with ETL and Fivetran or Matillion.
Proficiency with Snowflake and complex Oracle data transformations.
Proficiency with JSON, CSV, APIs, and SFTP.
Proficiency with SQL and Python.
Proficiency with AWS Cloud Services.
Proficiency with GitHub administration.
Experience with Agile/Scrum SDLC.

Responsibilities

Lead the design, development, and maintenance of ETL processes using Snowflake and AWS Cloud Services.
Extract structured and semi-structured commercial datasets from Oracle source systems into Snowflake cloud data warehouses.
Use Fivetran to support data extraction, transformation, and loading.
Improve business data pipelines for efficiency, performance, and scalability.
Use BigQuery to execute complex data transformations for marketing teams.
Create dashboards using Looker.
Develop custom frameworks using SFTP and APIs to handle CSV, JSON, and relational database data.
Manage data codebase integrity, pipeline version control, and software deployment using GitHub.
Create frameworks for data transformations across structured and unstructured formats, with automated scheduling and monitoring.
Generate and troubleshoot advanced code using SQL and Python.
Implement automated data quality checks and validation processes.
Work with commercial product managers to ensure accurate and reliable data delivery.
Document ETL processes, data models, and framework functionality.
Stay current with emerging data engineering technologies and trends.