Job DescriptionThe Analytics Engineer plays a key role in designing, building, and maintaining the data assets that power analytics, reporting, and AI-driven initiatives across the organization. This individual bridges data engineering and business intelligence-transforming raw healthcare data into trusted, analytics-ready models and scalable insights. The ideal candidate will be fluent in PySpark, SQL, and modern data modeling techniques, with a strong understanding of healthcare data standards and the analytical needs of clinical and operational stakeholders.
Key ResponsibilitiesData Engineering and Modeling
- Develop and optimize data transformation workflows in PySpark and SQL to prepare data for analytics and reporting.
- Design, maintain, and document semantic models and data marts in alignment with enterprise data architecture (e.g., medallion or layered lakehouse design).
- Collaborate with data governance and quality teams to ensure adherence to standards, lineage, and DQA processes.
- Automate and orchestrate data refresh processes for analytics environments.
Analytics Enablement
- Build efficient and reusable data models to support Power BI and AI/ML use cases.
- Partner with analysts, data scientists, and business leaders to ensure reliable access to curated, high-quality data.
- Build and maintain enterprise reports and dashboard including measures, KPIs, and business logic that populates them.
Healthcare Data & Compliance
- Work with FHIR, HL7, and other healthcare data standards to harmonize and integrate data across systems.
- Implement best practices for HIPAA compliance, privacy, and secure data handling within all analytics workflows.
Innovation and Continuous Improveme
nt- Contribute to the modernization of analytics infrastructure, enabling AI and predictive analytics readiness.
- Explore and prototype new tools or frameworks to improve efficiency, reliability, or insight delivery.
Required Qualifications:- Bachelor's degree in Data Science, Computer Science, Healthcare Informatics
- 3+ years of experience in data engineering, analytics development, or BI engineering (healthcare experience preferred).
- Proficiency in PySpark, SQL, and DAX for data preparation and transformation.
- Experience with Power BI or similar BI tools for semantic modeling and visualization.
- Understanding of healthcare data standards (FHIR, HL7, OMOP) and compliance frameworks (HIPAA).
- Experience working in Agile or DevOps environments.
Preferred Qualifications- Familiarity with modern data platforms such as Microsoft Fabric, Databricks, or Azure Synapse.
- Experience integrating analytics workflows with AI/ML solutions.
- Knowledge of version control, CI/CD, and environment-based deployment practices.
- Advanced degree in Data Science, Computer Science, Healthcare Informatics, or related field
Compensation is determined based on years of relevant experience and departmental equity.
