Senior Data & AI Engineer

Join Arizona’s largest, most prominent not-for-profit hospice, serving the valley since 1977.

Hospice of the Valley is a national leader in hospice care and has been serving the Phoenix metropolitan area since 1977. A mission-driven, not-for-profit organization, Hospice of the Valley employs compassionate, skilled professionals who are committed to excellence, enjoy teamwork, and contribute daily to our mission and culture of caring. Team members experience a friendly, supportive atmosphere, leadership support, autonomy, flexibility, and the privilege of doing meaningful, rewarding work.

• Supportive work environment with a culture of caring for patients and one another.
• Competitive wages and excellent benefit program.
• Generous Paid Time Off.
• Flexible schedules for work/life balance.

The Senior Data & AI Engineer will need to have deep hands ‑ on experience in Snowflake, Microsoft Fabric (incl. One Lake), and healthcare data ecosystems. The ideal candidate understands data modeling, data integration, and data transformation across structured and unstructured sources, and can build machine learning pipelines that operate on claims and clinical data. You’ll design secure, scalable data platforms;

map and normalize data across payers, providers, CMS datasets, EHR systems, and HIEs; and operationalize AI tools to drive measurable outcomes in cost, quality, and member/patient experience.

• Architect, implement, and optimize data solutions in Snowflake and Microsoft Fabric (incl. One Lake, Lake houses, Warehouses, and Data Engineering pipelines).
• Build robust ingestion frameworks for batch and streaming data (e.g., ADLS, Event Hub, APIs, SFTP) with lineage and governance.
• Manage data security, privacy, and compliance (HIPAA/PHI; role ‑ based access, masking, tokenization, de ‑ identification ).

• Design conceptual/logical/physical models (normalized, dimensional/star, data vault where appropriate).
• Implement data mapping and transformations for structured (claims, eligibility, provider, enrollment) and unstructured (clinical notes, PDFs) data.
• Harmonize healthcare data using FHIR/HL7/ C ‑ CDA , X12/EDI 837/835, NCPDP, and CMS standards; reconcile and link records across EHR and HIE sources.
• Build ML pipelines for risk stratification, cost/utilization forecasting, fraud/waste/abuse detection, quality measure computation (e.g., HEDIS), and care gap identification.
• Operationalize models with MLOps (experiment tracking, reproducibility, CI/CD, monitoring, drift detection).
• Leverage LLMs/AI tools for data quality, entity resolution, summarization, and clinical insights—ensuring safety, bias checks, and auditability.

• Implement data cataloging, lineage, and metadata (e.g., Microsoft Purview or equivalent).
• Establish quality SLAs, validation rules, profiling, and automated anomaly detection.
• Instrument pipelines for cost, performance, and reliability (e.g., Snowflake resource monitors, Fabric capacities).
• Work with product owners, clinicians, actuaries, and analytics teams to translate requirements into scalable solutions.
• Produce clear documentation, data dictionaries, and mapping specs; mentor engineers and analysts.
• Contribute to architectural roadmaps, reference patterns, and best practices across the enterprise.

Maintains and enhances professional skills.

Adheres to high standards of personal and professional conduct.

• 8+ years in data engineering/analytics; 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 One Lake, Lake houses, Warehouses, Dataflows Gen2, Notebooks, Pipelines; capacity management).
• Data integration & transformation proficiency: SQL (advanced), dbt or Fabric Dataflows/Power Query M, ADF/Synapse/Fabric Pipelines, Python for ETL/ELT.
• Mapping from CMS data (e.g., Medicare datasets, claims/encounters), X12/EDI, FHIR/HL7, provider and eligibility.
• Experience with structured (tables, CSV, Parquet) and unstructured (clinical notes, PDFs, blobs)…