Associate Ai Engineer Jobs in Arizona (NOW HIRING)

Job Summary:
Ryan House is Arizona's largest, most prominent not-for-profit hospice, serving the valley since 1977. The Senior Data & AI Engineer will be responsible for architecting and optimizing data solutions, building machine learning pipelines, and ensuring data security and compliance within healthcare data ecosystems.
Responsibilities:
• Architect, implement, and optimize data solutions in Snowflake and Microsoft Fabric (incl. OneLake, Lakehouses, Warehouses, and Data Engineering pipelines).
• Build robust ingestion frameworks for batch and streaming data (e.g., ADLS, EventHub, 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.
Qualifications:
Required:
• 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 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 & 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) data; NLP pipelines (optional but valued)
• Machine learning: feature engineering, model training/evaluation, and deployment (e.g., scikit-learn, PyTorch/TensorFlow, Fabric ML/Notebook, Azure ML); production monitoring
• Security & compliance: HIPAA, PHI handling, auditing, data residency, BAAs; practical access control in Snowflake/Fabric
• Strong communication; ability to author mapping specs, lineage docs, and present trade-offs to technical and non-technical stakeholders
Preferred:
• Interoperability: FHIR R4, HL7 v2, X12/EDI (837/835), NCPDP; experience with HIEs and EHR integrations (Epic, Cerner, etc.)
• CMS & payer/provider data: Medicare fee-for-service, MA, Medicaid, CCW, APCD, and quality programs; risk adjustment (HCC), HEDIS measures
• MLOps & DevOps: MLflow, DVC, GitHub Actions/Azure DevOps, containerization (Docker), orchestration (Airflow, Fabric Pipelines, or ADF)
• Governance: Microsoft Purview (catalog, lineage, classifications), data quality tools
• Visualization: Power BI and Fabric Direct Lake; semantic modeling and row-level security
• Cloud: Azure (ADLS, Event Hub, Functions, Key Vault, Databricks), optional AWS/GCP exposure
• Certifications: Snowflake SnowPro Core/Advanced, Microsoft Certified (Azure Data Engineer Associate, Fabric Analytics Engineer)
Company:
Ryan House provides pediatric respite care, therapeutic activities, and end-of-life care. Founded in 2003, the company is headquartered in Phoenix, USA, with a team of 11-50 employees. The company is currently Early Stage.