Senior Data Engineer - Microsoft Fabric & Healthcare Integrations

We are a growing multi-site healthcare organization building a centralized data and analytics platform to support better operational decision-making, reporting, automation, and future AI initiatives.

We are looking for a hands-on Senior Data Engineer to lead the development of this data foundation.

This is not primarily a reporting or dashboard development role. You will be responsible for designing, building, and maintaining the infrastructure that moves data from our core operational systems-including our electronic health record (eClinicalWorks) and CRM (HubSpot)-into Microsoft Fabric.

You will have significant ownership over how our data platform is designed from the beginning and will work directly with operational and technical stakeholders to turn fragmented healthcare and business data into reliable, reusable data products.

What You Will Build

Your initial focus will be establishing our Microsoft Fabric environment and creating a scalable data architecture that can support the organization long term.

You will:

• Design and implement our Microsoft Fabric data architecture using OneLake, Lakehouse/Warehouse, Data Factory pipelines, notebooks, and related Fabric services.
• Build and maintain data ingestion pipelines from eClinicalWorks, HubSpot, APIs, databases, files, and future enterprise systems.
• Work with REST APIs, FHIR APIs, webhooks, batch exports, and other integration methods to reliably extract source-system data.
• Establish raw, validated, and analytics-ready data layers using a medallion-style architecture.
• Clean, standardize, deduplicate, and reconcile data across systems.
• Develop data models for patients, referrals, appointments, providers, procedures, cases, outcomes, and other operational entities.
• Develop methods for matching records across systems when identifiers are inconsistent or unavailable.
• Create reusable curated datasets that support Power BI reporting, operational analytics, automation, and future AI applications.
• Implement incremental loading, change detection, schema management, error handling, logging, alerting, and pipeline monitoring.
• Establish data quality checks and processes for identifying incomplete, inconsistent, or unexpected source data.
• Implement appropriate security, access controls, and governance practices for healthcare data.
• Use Git and CI/CD practices so data pipelines and transformations are version-controlled, documented, and maintainable.
• Monitor Fabric usage, performance, capacity, and cost as the platform grows.
• Document architecture, data definitions, pipelines, dependencies, and operating procedures.
• Maintain and improve the platform after the initial implementation rather than treating the project as a one-time migration.

First 6-12 Month Priorities

A successful candidate should be able to take ownership of the platform from architecture through production.

Early priorities will include:

• Assess our existing systems, data sources, reporting requirements, and Microsoft environment.
• Design and configure the initial Microsoft Fabric architecture.
• Establish secure and reliable ingestion from HubSpot and eClinicalWorks.
• Create a raw historical data layer that preserves source-system data.
• Build cleaned and standardized datasets that reconcile information across systems.
• Create an initial analytics-ready data model for high-priority operational reporting.
• Implement automated pipeline monitoring, data-quality validation, documentation, and recovery processes.
• Establish engineering standards that allow additional data sources and use cases to be added without rebuilding the platform., Power BI knowledge is useful, but the primary responsibility is building the reliable data infrastructure underneath reporting, analytics, automation, and AI applications.

We need someone comfortable working at the level of APIs, pipelines, Python, SQL, data models, cloud architecture, security, and production operations.

What Success Looks Like

Within the first year, we want to have a maintainable Microsoft Fabric environment where data from our major systems is automatically collected, validated, standardized, and made available through trusted datasets.

Instead of analysts repeatedly extracting and cleaning data manually, the organization should be able to rely on centralized datasets with clearly defined metrics and lineage.

The platform should also be designed so additional sources, analytics use cases, automation, and AI capabilities can be added over time without rebuilding the underlying infrastructure.

Why This Role Is Different

You will be joining at the beginning of our data platform build rather than maintaining an architecture that has already been established.

You will have significant influence over the architecture, engineering standards, data models, and technologies that become the foundation for how the organization uses data going forward.

This is a strong fit for someone who enjoys building systems, solving difficult integration problems, and owning a data platform end-to-end.

Pay: $125,000.00 - $150,000.00 per year

We are looking for someone who has actually built and operated modern data platforms, not someone whose experience is primarily reporting or visualization.

Strong candidates should have:

• 4+ years of professional data engineering, data platform, or data integration experience.
• Hands-on experience building production solutions with Microsoft Fabric or a closely related Azure data stack.
• Strong SQL skills.
• Strong Python and/or PySpark skills.
• Experience designing ETL/ELT pipelines and data ingestion frameworks.
• Experience with Microsoft Fabric Lakehouse, OneLake, Data Factory/Pipelines, notebooks, Delta tables, or equivalent technologies.
• Experience integrating third-party systems through REST APIs.
• Experience implementing incremental data loads rather than relying only on full data refreshes.
• Strong understanding of dimensional modeling, relational modeling, lakehouse architecture, and analytics-oriented data modeling.
• Experience troubleshooting API authentication, pagination, rate limits, schema changes, malformed records, pipeline failures, and other real-world integration issues.
• Experience with Git, source control, and CI/CD practices.
• Experience implementing monitoring, logging, data-quality validation, and alerting for production pipelines.
• Ability to work independently and make practical architectural decisions in an environment where the data platform is still being built.

Healthcare / Integration Experience

Healthcare experience is strongly preferred.

Experience with any of the following would be particularly valuable:

• Healthcare EHR/EMR data
• eClinicalWorks
• FHIR / HL7
• Healthcare operational or clinical data models
• HIPAA-regulated data environments
• Patient identity matching or Master Patient Index concepts
• HubSpot APIs and CRM data
• Microsoft Entra ID and Azure security
• Microsoft Purview or other data governance tools
• Power BI semantic models

Direct eClinicalWorks experience is a major plus but is not required if you have strong healthcare API/FHIR integration experience and can quickly learn unfamiliar source systems.

• 401(k)
• 401(k) matching
• Dental insurance
• Health insurance
• Life insurance
• Paid time off
• Vision insurance