Bachelor's Degree and 4+ years in healthcare analytics or related field.
3+ years of experience in data pipelines and reporting solutions using healthcare data.
Strong expertise in SQL, Python, and Databricks for data engineering and automation.
Experience in ETL/ELT processes for large healthcare datasets.
Proficiency in data modeling and relational database design.
Responsibilities
Design and develop scalable data pipelines and integration processes.
Collaborate with business stakeholders to understand data requirements.
Solve complex data quality and performance issues.
Support strategic initiatives through automated workflows and analytics.
Participate in cross-functional teams to deliver data solutions.
Benefits
Comprehensive healthcare and dental coverage.
Retirement savings plan with employer matching.
Opportunities for professional development and training.
Flexible work arrangements and a supportive work environment.
Access to wellness programs and resources.
Full Job Description
JOB REQUIREMENTS
Bachelor's Degree and 4+ years of experience in healthcare analytics, healthcare services, statistical analysis, data engineering, business intelligence, insurance economics, or a related field.
3+ years of experience designing, developing, and supporting data pipelines, data integration processes, and reporting solutions utilizing healthcare and pharmacy data.
Strong experience with SQL, Python, Databricks, and modern data engineering frameworks for data transformation, automation, and analytics.
Experience developing, maintaining, and optimizing ETL/ELT processes to support large-scale healthcare, claims, pharmacy, and population health datasets.
Proficiency in data modeling, relational database design, data warehousing concepts, and creation of data marts that support reporting and analytics initiatives.
Experience working with cloud-based data platforms and distributed computing environments to process and analyze large datasets efficiently.
Partners with business stakeholders, analysts, and technology teams to understand data requirements and deliver scalable data solutions.
Solves moderately complex to complex business and technical problems with a focus on data quality, performance, scalability, and reliability.
Supports strategic initiatives through the development of trusted data assets, automated workflows, and self-service analytics capabilities.
Participates in cross-functional project teams to deliver data solutions, enhancements, and operational improvements aligned with organizational objectives.
Demonstrates understanding of healthcare data structures including claims, eligibility, pharmacy, provider, and population health data domains.
Applies data governance, security, and regulatory compliance standards when managing healthcare data assets.
Supports data framework for dashboards, ac hoc analysis, and downstream data deliveries.
Supoort with complex data inquiries and data profiling.
PREFERRED REQUIREMENTS
Advanced SQL expertise, including complex joins, window functions, query optimization, stored procedures, and performance tuning.
Strong experience with Databricks, Spark, Delta Lake, and distributed data processing frameworks.
Strong Python programming skills for data engineering, automation, data quality monitoring, and analytics enablement.
Experience building and orchestrating ETL/ELT pipelines using tools such as Databricks Workflows, Airflow, Azure Data Factory, or similar technologies.
Experience developing scalable data lake, data warehouse, and data mart solutions that support enterprise reporting and analytics.
Knowledge of healthcare data standards and structures, including medical claims, pharmacy claims, member eligibility, provider, and population health data.
Experience creating and supporting semantic layers, reporting datasets, and business intelligence solutions using Power BI, Tableau, or similar platforms.
Familiarity with CI/CD practices, source control management (Git), automated testing, and DevOps concepts for data platforms.
Experience implementing data quality frameworks, monitoring processes, and production support practices.
