Hybrid Senior Healthcare Data Engineer; W2

Type of Role:
Contract to Hire; W2-Benefits Eligible

Rate: $60-$65

Hybrid in Downtown Chicago

We cannot work C2C or 1099

No Sponsorship or Visa Transfer available

We are seeking an experienced Senior Healthcare Data Engineer to design, develop, and support scalable data solutions using healthcare, pharmacy, claims, and population health data. This position will build reliable data pipelines, improve data quality, and create trusted datasets that support reporting, analytics, and strategic business initiatives.

The ideal candidate combines strong SQL, Python, and Databricks expertise with a solid understanding of healthcare data. You will partner with business stakeholders, analysts, and technology teams to translate complex requirements into secure, reliable, and high-performing data solutions.

• Design, develop, and support scalable data pipelines and integration processes for healthcare and pharmacy data.
• Build, maintain, and optimize ETL/ELT workflows supporting claims, eligibility, pharmacy, provider, and population health datasets.
• Use SQL, Python, Databricks, Spark, and modern data engineering frameworks to transform, automate, and analyze large datasets.
• Create and maintain data models, data marts, reporting datasets, and semantic layers for enterprise analytics.
• Develop the data foundation needed for dashboards, ad hoc analysis, self-service reporting, and downstream data deliveries.
• Partner with business stakeholders, analysts, and technology teams to understand requirements and deliver practical, scalable solutions.
• Conduct complex data analysis, data profiling, and investigation to resolve business and technical questions.
• Identify and resolve data-quality, performance, scalability, and reliability issues.
• Develop automated workflows and trusted data assets that support strategic and operational initiatives.
• Participate in cross-functional project teams delivering new solutions, enhancements, and process improvements.
• Apply appropriate data governance, privacy, security, and regulatory standards when working with healthcare information.
• Support data-quality monitoring, production operations, troubleshooting, and continuous improvement.

• Bachelor’s degree in data science, computer science, information systems, statistics, healthcare analytics, economics, or a related field.
• Four or more years of experience in healthcare analytics, healthcare services, data engineering, business intelligence, statistical analysis, insurance economics, or a related area.
• Three or more years of experience designing, developing, and supporting data pipelines, data integrations, and reporting solutions using healthcare or pharmacy data.
• Strong hands‑on experience with SQL, Python, and Databricks.
• Experience developing and optimizing ETL/ELT processes for large and complex datasets.
• Knowledge of relational database design, data modeling, data warehousing, and data‑mart development.
• Experience working with cloud‑based data platforms or distributed computing environments.
• Understanding of healthcare data domains such as medical claims, pharmacy claims, member eligibility, provider, and population health data.
• Strong analytical, problem‑solving, and communication skills.

• Advanced SQL skills, including complex joins, window functions, stored procedures, query optimization, and performance tuning.
• Experience with Databricks, Apache Spark, Delta Lake, and distributed data‑processing frameworks.
• Advanced Python skills related to data engineering, automation, data‑quality monitoring, and analytics enablement.
• Experience orchestrating pipelines with Databricks Workflows, Apache Airflow, Azure Data Factory, or similar tools.
• Experience designing enterprise data lakes, data warehouses, and data marts.
• Experience supporting semantic layers and business intelligence solutions using Power BI, Tableau, or comparable platforms.
• Familiarity with Git, CI/CD, automated testing, and Dev Ops practices for data platforms.
• Experience implementing data‑quality frameworks, monitoring processes, and production‑support procedures.
• Knowledge of healthcare data governance, security, privacy, and regulatory requirements.