IT Data Engineer III - Remote

Paradigm is an accountable specialty care management organization focused on improving the lives of people with complex injuries and diagnoses. The company has been a pioneer in value-based care since 1991 and has an exceptional track record of generating the very best outcomes for patients, payers, and providers. Deep clinical expertise is the foundation for every part of Paradigm’s business: risk-based clinical solutions, case management, specialty networks, home health, shared decision support, and payment integrity programs.

We’re proud to be recognized—again! For the fourth year in a row, we’ve been certified by Great Place to Work®, and for the third consecutive year, we’ve earned a spot on Fortune's Best Workplaces in Health Care™ list. These honors reflect our unwavering commitment to fostering a positive, inclusive, and employee-centric culture where people thrive.

Watch this short video for a brief introduction to Paradigm.


We are seeking a full-time, remote Data Engineer III position. This role supports the continued proliferation of data-driven decision-making throughout Paradigm by designing, building, and maintaining robust data pipelines and architectures. The Data Engineer ensures that clean, reliable, and well-structured data is readily available to analysts, data scientists, and other key stakeholders for advanced analytics, reporting, and operational needs. The ideal candidate has a strong technical background in data integration, data modeling, and modern data engineering tools — specifically Microsoft Power BI, Microsoft Fabric, and a variety of ETL/ELT platforms — along with demonstrated experience working independently to prioritize data projects. Familiarity with healthcare and/or workers’ compensation terminology and business concepts is a plus.

RESPONSIBILITIES:

1. Design and Maintenance of Data Architectures
◦ Architect, build, and optimize Paradigm’s data pipelines, data lake, and data warehouse environments, ensuring efficient ingestion of data from SQL Server, and other sources.
◦ Incorporate modern data platform technologies such as Microsoft Fabric where appropriate, to enhance scalability and performance.
2. Develop and Optimize Data Pipelines
◦ Develop and maintain efficient ETL/ELT processes using tools like Azure Data Factory, SSIS, or equivalent platforms.
◦ Leverage robust integration tools to automate data flows and ensure data quality.
◦ Monitor and optimize these pipelines for performance, scalability, and reliability.
3. Collaborate with Cross-Functional Teams
◦ Work independently with departmental leaders, business users, and analytics teams to define data requirements and prioritize projects with the highest ROI.
◦ Partner closely with database administrators, BI developers, data scientists, and application teams to ensure data availability and alignment with business goals.
◦ Support and collaborate on Power BI initiatives, enabling self-service analytics.
4. Data Governance and Documentation
◦ Develop and maintain comprehensive documentation for data pipelines, data models, and data governance processes.
◦ Produce and update a data dictionary to facilitate the use of self-service analytics tools by non-technical business users.
5. Implement Data Quality and Security Controls
◦ Enforce data governance, security policies, and access controls to ensure data confidentiality, integrity, and compliance with regulatory requirements.
◦ Configure and maintain role-based and object-level security for data pipelines, warehouses, and analytics tools.
6. Change Management and Best Practices
◦ Document and refine data engineering change management policies, aligning with industry best practices to maintain stable, secure, and version-controlled environments (e.g., using Azure DevOps, AWS Pipelines, or similar tools).
7. Evaluate and Implement New Technologies
◦ Research and recommend new data engineering tools, frameworks, and solutions, with a particular focus on the Microsoft technology stack (e.g., Microsoft Fabric, Power BI).
◦ Maintain awareness of industry trends to inform Paradigm’s strategic data architecture decisions.
8. Support Ad Hoc Data Needs
◦ Work closely with business users on ad hoc data requests, troubleshooting data issues, and providing solutions in a timely manner.
9. Production Support and Monitoring
◦ Proactively monitor and troubleshoot data pipelines and integrations across SQL Server, DB2, Oracle, and cloud environments to minimize downtime.
◦ Quickly resolve incidents to ensure seamless data availability.
10. Champion Data-Driven Culture
◦ Advocate for data best practices across the organiza