Design, build, and implement critical components of the enterprise data platform
Develop ETL and data pipeline capabilities
Write dynamic, parameterized, and reusable PySpark code
Implement Azure DevOps CI/CD pipelines for all data solutions
Apply Test Driven Development methodology to all data solutions
Lead the implementation of outcomes, recommendations, and designs from Data Governance and Enterprise Architecture
Perform data exploration and data profiling with tools such as SSAS
Provide technical mentorship to team members
Collaborate with product owners and business stakeholders

8+ years’ experience with data engineering specifically in Extract, Transform and Load (ETL) concepts and processes
5+ years’ experience designing, implementing, and supporting cloud data solutions
Bachelor’s degree in engineering or related field
Expert level experience with at least one RDBMS and query language such as T-SQL, PL/SQL, Spark SQL
Certifications within Azure such as Azure Fundamentals, Azure Fabric Data Engineer, Azure Data Scientist, and/or Azure DevOps Engineer
Excellent communication skills both verbal and written
Experience in Agile, SAFe, and/or Scrum is preferred
Experience integrating with data quality, data catalog and data lineage tools is preferred

Senior Data Engineer

Key skills