The Senior Data & AI Engineer will architect and optimize secure, scalable data platforms and deliver machine learning pipelines grounded in healthcare claims and clinical data to support cost, quality, and member/patient outcomes.
Key Responsibilities
- Architect, implement, and optimize data solutions in Snowflake and Microsoft Fabric, including OneLake, Lakehouses, Warehouses, and data engineering pipelines.
- Build ingestion frameworks for batch and streaming sources using technologies such as ADLS, EventHub, APIs, and SFTP, with lineage and governance.
- Manage data security, privacy, and compliance for HIPAA and PHI, including role-based access, masking, tokenization, and deidentification.
- Design conceptual, logical, and physical data models, using patterns such as normalized, dimensional/star, and data vault where appropriate.
- Implement data mapping and transformations for both structured (claims, eligibility, provider, enrollment) and unstructured data (clinical notes, PDFs).
- Harmonize healthcare data using FHIR/HL7/CCDA, X12/EDI 837/835, NCPDP, and CMS standards, including record reconciliation and linking across EHR and HIE sources.
- Develop ML pipelines for risk stratification, cost/utilization forecasting, fraud/waste/abuse detection, quality measure computation (e.g., HEDIS), and care gap identification.
- Operationalize models using MLOps, including experiment tracking, reproducibility, CI/CD, monitoring, and drift detection.
- Leverage LLMs/AI tools for data quality, entity resolution, summarization, and clinical insights, while ensuring safety, bias checks, and auditability.
- Implement data cataloging, lineage, and metadata management (for example, Microsoft Purview or an equivalent approach).
- Set up data quality SLAs, validation rules, profiling, and automated anomaly detection.
- Instrument pipelines for cost, performance, and reliability using mechanisms such as Snowflake resource monitors and Fabric capacities.
- Partner with product owners, clinicians, actuaries, and analytics teams to translate requirements into scalable solutions.
- Create clear documentation, including data dictionaries and mapping specifications, and mentor engineers and analysts.
- Contribute to enterprise architectural roadmaps, reference patterns, and best practices.
Minimum Qualifications
- 8+ years in data engineering/analytics, including 5+ years hands-on with Snowflake (compute, storage, virtual warehouses, tasks, streams, Snowpipe, Time Travel, RBAC, row/column masking, data sharing, Dynamic Tables).
- 2+ years with Microsoft Fabric (including OneLake, Lakehouses, Warehouses, Dataflows Gen2, Notebooks, Pipelines; capacity management).
- Strong data modeling expertise (dimensional/star, 3NF, data vault; surrogate keys, SCD types, conformed dimensions).
- Data integration and transformation proficiency: advanced SQL, dbt or Fabric Dataflows/Power Query M, ADF/Synapse/Fabric Pipelines, and Python for ETL/ELT.
- Experience mapping CMS data (e.g., Medicare datasets, claims/encounters), plus X12/EDI, FHIR/HL7, provider and eligibility.
- Experience with structured data (tables, CSV, Parquet) and unstructured data (clinical notes, PDFs, blobs), including NLP pipelines (optional but valued).
- Machine learning capabilities: feature engineering, model training/evaluation, and deployment (for example, scikit-learn, PyTorch/TensorFlow, Fabric ML/Notebook, Azure ML) with production monitoring.
- Security and compliance experience covering HIPAA and PHI handling, auditing, data residency, and BAAs, including practical access control in Snowflake/Fabric.
- Strong communication skills, including the ability to author mapping specs and lineage documentation and present tradeoffs to technical and nontechnical stakeholders.
Preferred Qualifications
- Interoperability experience with FHIR R4, HL7 v2, X12/EDI (837/835), NCPDP, and familiarity with HIE and EHR integrations (e.g., Epic, Cerner).
- Experience with CMS and payer/provider datasets (Medicare fee-for-service, MA, Medicaid, CCW, APCD, quality programs), including risk adjustment (HCC) and HEDIS measures.
- MLOps and DevOps exposure, including MLflow, DVC, GitHub Actions/Azure DevOps, containerization (Docker), and orchestration (e.g., Airflow, Fabric Pipelines, or ADF).
- Governance tooling experience such as Microsoft Purview (catalog, lineage, classifications) and data quality tools.
- Visualization experience with Power BI and Fabric Direct Lake, including semantic modeling and row-level security.
- Cloud exposure in Azure (ADLS, Event Hub, Functions, Key Vault, Databricks), with optional AWS/GCP familiarity.
- Relevant certifications, including Snowflake SnowPro Core/Advanced and Microsoft Certified roles such as Azure Data Engineer Associate and Fabric Analytics Engineer.
Technologies
Snowflake, Microsoft Fabric, OneLake, Lakehouses, Warehouses, data engineering pipelines, ADLS, EventHub, APIs, SFTP, HIPAA, PHI, FHIR, HL7, CCDA, X12/EDI 837/835, NCPDP, CMS standards, EHR, HIE, MLOps, LLMs, Microsoft Purview, Power Query M, ADF, Synapse, dbt, Python, SQL, Dataflows Gen2, Notebooks, Fabric Pipelines, RBAC, Dynamic Tables, Snowpipe, Time Travel, data vault, dimensional/star, 3NF, scikit-learn, PyTorch, TensorFlow, Fabric ML, Azure ML, Snowflake resource monitors, Fabric capacities, MLflow, DVC, GitHub Actions, Azure DevOps, Docker, Airflow, Power BI, Fabric Direct Lake, row-level security, Azure, Event Hub, Functions, Key Vault, Databricks.
Benefits
- Supportive work environment with a culture of caring for patients and one another.
- Competitive wages and an excellent benefit program.
- Generous Paid Time Off.
- Flexible schedules for work/life balance.
Location and Experience
Phoenix, AZ (onsite). Minimum of 8 years of relevant experience.
