Senior Cloud Data Engineer
$100k - $150kHealthDrive Corporation
Overview At HealthDrive, we help improve quality of life for older adults who may otherwise have limited access to specialized care. For more than 30 years, HealthDrive has been a trusted clinical partner to senior living communities nationwide. The Senior Cloud Data Engineer is a senior technical role responsible for operating, enhancing, and extending HealthDrive’s cloud data platform on Microsoft Azure and Microsoft Fabric. The role builds and maintains the pipelines and data models that bring HealthDrive’s clinical, operational, and financial data together into a trusted, analytics-ready foundation — including the claims and encounter data that sit at the center of how HealthDrive measures cost, quality, and performance. This is hands‑on healthcare data engineering, and it is a design role as much as a build role. The engineer is expected to architect and design solutions — translating business problems into technical approaches and setting technical direction — rather than working to specifications handed down by others. Success depends less on any single tool than on genuine command of healthcare data and its real‑world complexity. The engineer works closely with the CIO, the Software Development Manager who owns the source data warehouse, the business analysis function, and the operations and finance teams. Salary: $100K - $150K. Compensation offered will depend on skill set, experience, and proven track record in similar roles. Responsibilities Solution design and architecture: Design and architect data solutions end-to-end — taking business problems from operations, finance, and clinical leadership, defining the technical approach, and then building it. This role sets technical direction for HealthDrive’s data platform. Data ingestion: Build and operate pipelines that bring clinical, operational, and financial data — including claims and encounters — from source systems into OneLake, using Fabric Data Factory, Azure Data Factory, and Spark notebooks. Source system integration: Source data reliably from HealthDrive’s on‑premises SQL Server data warehouse and other operational systems, including incremental and change‑data‑capture patterns. Data transformation: Maintain and extend the standardized clinical, operations, and finance data model across the medallion architecture, and develop new data models as the business requires. Data quality and reconciliation: Build the validation, reconciliation, and exception handling that healthcare data requires to be trusted for clinical, operational, and financial reporting. Certified semantic models: Develop and maintain gold‑layer, certified semantic models in Microsoft Fabric that the business analysis and reporting functions build from. Business metric definitions: Establish and maintain canonical definitions for HealthDrive’s core business metrics so the organization works from a single source of truth. Data governance and PHI: Apply access controls, classification, and lineage — including Microsoft Purview — to protect PHI and meet HIPAA obligations. Partnership: Partner with the CIO, the Software Development Manager (owner of the source data warehouse), the business analysis function, and the operations and finance teams to translate business questions into durable data assets. Qualifications Must Have 5+ years of hands‑on data engineering experience. 3+ years on the Microsoft Azure data platform — Azure Data Factory, Synapse, and ADLS Gen2. Strong Python and PySpark, and strong SQL. Healthcare data engineering across claims, encounters, clinical, operational, and financial data — including the reconciliation and data‑quality work the domain demands. Experience sourcing data from on‑premises SQL Server environments. Working knowledge of lakehouse and medallion architecture. Demonstrated ability to design and architect data solutions independently — owning the technical approach from problem to production, not solely executing someone else’s design. Ability to explain data models and metric definitions clearly to non‑technical partners in operations and finance. Strongly Preferred Microsoft Fabric — OneLake, Lakehouse, and Fabric Warehouse. HealthDrive builds on Fabric; strong Azure data platform engineers will be supported in ramping onto it. dbt for transformation and testing. Value‑Based Care fluency — both the clinical and the financial side, including total cost of care, shared savings, risk adjustment, PMPM, and quality‑linked reimbursement. Candidates with strong healthcare data engineering and the appetite to learn the financial mechanics will be supported in developing this. Provider or health‑system experience (preferred over payer‑side experience). Nice to have Snowflake, or Databricks on Azure. Power BI and semantic model development. Microsoft Purview and PHI data governance tooling. Machine learning or generative AI applied to healthcare data Education And Qualifications Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field — or equivalent practical experience. 5+ years of professional data engineering experience, including healthcare data. Certifications And Licenses (Preferred) Microsoft Certified: Fabric Analytics Engineer Associate (DP-600).
- Preferred) Microsoft Certified: Azure Data Engineer Associate (DP-203).
- Nice to have) Microsoft Certified: Power BI Data Analyst Associate (PL-300); Azure AI Engineer Associate (AI-102).
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