Data Engineer

• Oversee the daily performance, stability, and upkeep of the data warehouse to ensure dependable access to trusted data
• Design, build, and refine data pipelines that move and transform information efficiently across multiple platforms
• Develop engineering solutions using Python, Spark, and Databricks to support large-scale data processing and analytics workloads
• Create and maintain SQL-based data structures and workflows that improve data quality, usability, and consistency
• Apply sound data modeling practices to organize datasets for reporting, analysis, and downstream application use
• Partner with cross-functional teams to understand integration needs and deliver scalable data solutions aligned with business priorities
• Support cloud-based data movement and orchestration processes, including work involving Azure Data Factory where needed
• Contribute to reporting and visualization readiness by preparing well-structured datasets for tools such as Power BI, Tableau, or Looker

• Extensive experience in data engineering with strong hands-on use of Python in production environments
• Solid background in SQL and data warehouse support, including writing and optimizing complex queries
• Practical experience with Apache Spark and Azure Databricks for distributed data processing
• Understanding of data modeling concepts and the ability to structure datasets for analytical use
• Familiarity with cloud-based data integration tools, including exposure to Azure Data Factory
• Working knowledge of visualization platforms such as Power BI, Tableau, or Looker
• Experience with Microsoft SQL technologies and comfort operating within Azure-based data ecosystems
• Exposure to C# is beneficial but not required

Exposure to C#

• Medical, vision, dental, and life and disability insurance
• 401(k) plan
• Free online training