Data Enablement Engineer

We are hiring a Data Enablement Engineer for the Operational Intelligence program at BlueCross BlueShield of Tennessee!

In this role, you will support the enterprise Process Improvement & Intelligent Automation function by designing, building, and evolving the data infrastructure that enables utilization analysis, capacity modeling, productivity measurement, and broader operational intelligence insights. You'll develop scalable data pipelines, transformations, and curated data layers that power workforce planning, staffing analysis, and enterprise performance analytics within a Databricks-based environment.

You'll partner across operations, IT, HR, and executive leadership to deliver data products that directly inform staffing, forecasting, performance management, and strategic decision-making. A key focus of this role is enabling how the organization measures the impact of AI and automation initiatives - delivering the data models and metrics used to quantify improvements in utilization, productivity, and cost.

This is a hands-on engineering role with ownership of core analytics infrastructure. You'll define how data moves across systems, design and optimize ETL/ELT processes, and implement validation and reconciliation logic to ensure reliable, consistent metrics. The ideal candidate brings strong experience with SQL, Python, and BI tools, is comfortable owning data products end-to-end, and can translate complex business needs into scalable, durable data solutions.

Note:

• This is a remote, work-from-home position, but the final round of interviews will take place on-site in our Chattanooga, TN office.
• Sponsorship is not available for this role., * Designs, develops, and maintains ETL/ELT data pipelines, transformations, and datasets using SQL, Python, and Databricks, including delivery of new capabilities and enhancements.
• Owns data models and curated data layers for a business domain, ensuring scalability, consistency, and alignment with established standards.
• Develops and maintains BI datasets, semantic models, and reporting solutions, optimizing performance and supporting new and evolving business needs.
• Defines and implements data validation and reconciliation processes within ETL/ELT frameworks, ensuring accuracy, consistency, and reliability of metrics.
• Partners with business stakeholders, IT, and AI teams to translate business needs into technical requirements, refine solution design, and deliver scalable ETL/ELT-driven data solutions.
• Produces and maintains clear documentation of data logic, transformations, and metric definitions, including end-to-end ETL/ELT workflows, ensuring alignment with standards and enabling reuse.

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or a related field, or equivalent professional experience. Equivalent experience is defined as 4 years of professional work experience in a corporate environment., * 3+ years of experience in designing, developing, and maintaining data and analytics solutions using SQL, Python, and Databricks, including orchestrating and optimizing data pipelines and analytical datasets.
• Experience with ETL/ELT frameworks, including designing and implementing pipelines and transformation
• Experience with BI tools (e.g., Power BI, Cognos) developing and optimizing semantic models and performance-optimized reporting solutions.
• Experience owning data pipelines, models, and metrics, and independently translating business needs into technical requirements to deliver new and enhanced data solutions.

Skills/Certifications

• Advanced proficiency in SQL and Python for building, optimizing, and maintaining data pipelines and analytical datasets.
• Advanced proficiency in BI tools (e.g., Power BI, Cognos), including development and optimization of semantic models, datasets, and reporting solutions.
• Strong understanding of relational database and data warehousing concepts, including designing scalable data models and structured data solutions.
• Proficient in Databricks or similar cloud analytics platforms, including orchestrating and optimizing data pipelines and scalable data workflows.
• Strong understanding of ETL/ELT processes, including designing pipelines, implementing transformation logic, and applying data quality controls.