Databricks Analytics

Translate business workflows into curated datasets, reusable data marts, standardized metrics, and AI-ready assets through rigorous Data Modeling.

Design and optimize transformation pipelines using Azure Data Factory, Databricks, and Microsoft Fabric, supporting a scalable Lakehouse architecture.

Develop feature engineering pipelines for risk scoring, readmission prediction, and utilization forecasting; build reusable Feature Store capabilities serving BI and AI/ML workloads.

Partner with data scientists and ML engineers to maintain consistency between training and inference datasets and embed predictive outputs into clinical and operational workflows.

Develop a trusted Semantic Layer, curated datasets, and dashboards using Power BI, Tableau, and Databricks, aligned with standardized metrics.

Normalize healthcare data using ICD-10, CPT, and NDC, applying validation and governance controls throughout delivery.

Deep healthcare data expertise and confidence interpreting claims, clinical, and operational datasets across payer or provider environments.

A collaborative approach to translating ambiguous business needs into maintainable data solutions and communicating technical concepts to diverse stakeholders.

Strong ownership of scalable analytics foundations, standardized metrics, and production-grade data pipelines., Bachelor’s degree in information technology, Computer Science, or a related field, or equivalent experience.

5+ years working with healthcare data in analytics engineering, data engineering, or related roles, including increasing ownership of analytics solutions.

Strong SQL proficiency and programming experience with Python or Scala for transformation, validation, and performance optimization.

Experience with cloud data platforms: Azure preferred; AWS or Google Cloud Platform acceptable, including distributed processing with Spark, orchestration tools, and data lakes or lakehouses.

Understanding of healthcare vocabularies, including SNOMED, and experience preparing ML-ready datasets.

Preferred Qualifications

Hands-on Databricks experience with notebooks, Delta Lake, and workflows.

Knowledge of CI/CD, infrastructure-as-code, and data platform automation.

Experience with healthcare integration engines such as Rhapsody and Mirth, plus Data Governance, HIPAA compliance, and PHI handling.

Thinking Minds’ client offers health, dental, vision, disability and life insurance, retirement benefits with company match, education and credential reimbursement, paid time off, holidays, volunteer time, and paid orientation and training.