Senior Analytics Engineer

Senior Analytics Engineer role at HarmonyCares, a national value-based provider of in-home primary care services headquartered in Troy, Michigan and operating home-based practices across 14 states. The position focuses on building scalable data solutions from claims, clinical, and operational healthcare datasets to support analytics, machine learning, and organizational decision-making. HarmonyCares brings personalized healthcare directly to patients who face access barriers and maintains an integrated, team-based care model.

Responsibilities

• Partner with clinical, operational, and business teams to analyze workflows and convert requirements into scalable data models, curated datasets, standardized metrics, and AI-ready assets.
• Break down complex data and AI needs into maintainable pipelines by clarifying assumptions and designing production-grade feature and transformation workflows.
• Design, build, and tune data transformation pipelines and analytics models on cloud platforms including Azure Data Factory, Databricks, and Microsoft Fabric.
• Create and maintain feature engineering pipelines that support machine learning applications such as risk scoring, readmission prediction, and utilization forecasting.
• Develop reusable data marts and feature stores for both BI reporting and AI/ML workloads.
• Collaborate with data scientists and ML engineers to assemble high-quality training datasets and maintain consistency between training and inference environments.
• Integrate AI/ML model outputs into clinical and operational processes through alerts, prioritization queues, and decision support tools.
• Build and refine semantic models, curated datasets, and dashboards in Databricks, Power BI, and Tableau aligned with standardized metrics and ML insights.
• Work directly with healthcare claims, clinical, and operational data to ensure accurate interpretation for analytics and machine learning purposes.
• Ingest, transform, and normalize healthcare data using standards such as ICD-10, CPT, and NDC to support interoperability.
• Complete additional job-related duties as assigned.

Requirements

• Bachelor’s degree in information technology, computer science, or a related field, or equivalent professional experience.
• Minimum five years of experience in analytics engineering, data engineering, or similar data roles with progressive responsibility for data modeling and analytics solutions, focused on healthcare data.
• Direct experience working with claims and clinical datasets in payer or provider settings and converting data into actionable insights.
• Experience designing and constructing scalable data models, curated data marts, and semantic layers for BI and analytics.
• Strong knowledge of healthcare data standards and vocabularies including ICD-10, CPT, and SNOMED and their use in analytics and interoperability.
• Hands-on experience with cloud data platforms, preferably Azure, and modern components such as data lakes or lakehouses, Databricks or Spark, and orchestration tools.
• Advanced SQL skills plus proficiency in Python or Scala for data transformation, validation, and performance tuning.
• Experience with feature engineering and preparation of ML-ready datasets, including training data assembly and pipeline support for predictive models.
• Proven ability to translate ambiguous business problems into structured, scalable data solutions.
• Prior work in a healthcare services, payer, or provider organization.
• Hands-on experience with Databricks including Spark, notebooks, Delta Lake, and workflows.
• Knowledge of CI/CD, infrastructure-as-code, or data platform automation.
• Experience with healthcare integration engines such as Rhapsody or Mirth.
• Familiarity with data governance, HIPAA compliance, and protected health information handling.

Benefits

• Health, dental, vision, disability, and life insurance.
• 401(k) retirement plan with company match.
• Tuition, professional license, and certification reimbursement.
• Paid time off, holidays, and volunteer time.
• Paid orientation and training.
• Compensation range of $130,000 to $185,000 per year, with individual packages determined by skill set, experience, and qualifications.