Data Engineering & Analytics Lead-Information Technology

Premium Health is seeking a highly skilled, hands-on Data Engineering & Analytics Lead to elevate our data capabilities, and build a scalable, modern data ecosystem that enables data-driven insights to enhance patientcare, optimize operations, and support strategic decision-making.

This role combines leadership with day-to-day engineering. The Data Engineering & Analytics Lead will design and implement our core data infrastructure, lead analytics initiatives, and collaborate with cross-functional teams to shape how data is used throughout the organization. The lead will serve as both a thought leader and a hands-on technical implementor, architecting our data environment, establishing data standards and governance, building pipelines and models, and developing analytics solutions, while growing and mentoring a small data function over time.

If you are passionate about leveraging data to drive meaningful insights and have a proven track record in data engineering, analytics, and leadership we invite you to join us on this exciting journey.

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Time Commitment:
· 40 hours per week (Monday – Friday)

· Exempt from over-time

· Hybrid Eligible

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Responsibilities:
Data Strategy & Leadership

· Collaborate with the CDIO and Director of Technology to define a clear data vision aligned with the organization's goals and execute the enterprise data roadmap.

· Serve as a thought leader for data engineering and analytics, guiding the evolution of our data ecosystem and championing data-driven decision-making across the organization.

· Build and mentor a small data team, providing technical direction and performance feedback, fostering best practices and continuous learning, while remaining a hands-on implementor.

· Define and implement best practices, standards, and processes for data engineering, analytics, and data management across the organization.

Data Architecture & Infrastructure

· Design, implement, and maintain a scalable, reliable, and high-performing modern data infrastructure, aligned with the organizational needs and industry best practices.

· Architect and maintain data lake/lakehouse, warehouse, and related platform components to support analytics, reporting, and operational use cases.

· Establish and enforce data architecture standards, governance models, naming conventions ,and documentation.

Data Engineering & Pipelines

· Develop, optimize, and maintain scalable ETL/ELT pipelines and data workflows to collect, transform, normalize, and integrate data from diverse systems.

· Implement robust data quality processes, validation, monitoring, and error-handling frameworks.

· Ensure data is accurate, timely, secure, and ready for self-service analytics and downstream applications.

Analytics Enablement & Business Intelligence

· Partner with clinical, operational, and business leaders to understand data needs and translate them into scalable analytical models and datasets.

· Develop and maintain dashboards, performance metrics (KPIs), and reporting solutions to support strategic and operational decision-making.

· Enable self-service analytics by building curated, trusted data assets and collaborating with BI resources to expand organizational insight capabilities.

Data Governance, Security, and Compliance

· Lead the development and implementation of data governance and data quality processes to ensure data accuracy, consistency, and reliability.

· Ensure compliance with healthcare regulations and data protection standards (e.g.,HIPAA), embedding privacy and security controls into all data workflows.

· Collaborate with IT and security teams to implement appropriate access controls, encryption, row-level security, and secure credential management.

Cross Functional Collaboration

· Work closely with IT, clinical, finance, and operational teams to ensure seamless integration of data solutions with existing systems and applications.

· Translate complex technical concepts into clear, actionable insights for non-technical stakeholders.

· Foster data literacy and cultivate analytical skillsets across the organization to strengthen data-driven culture and decision making.

· Communicate insights and recommendations effectively to executive stakeholders, translating findings into actionable insights understandable by non-technical stakeholders.

Innovation & Continuous Improvement

· Evaluate emerging tools, technologies, and architectural patterns to identify opportunities for innovation and operational improvement.

· Continuously improve pipeline performance, data reliability, data modeling practices, and platform scalability.

· Stay current with trends in data engineering, analytics, cloud platforms, and healthcare technology.

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Requirements:
· Bachelor'sdegree in Computer Science, Engineering, or a related field. Master's degreepreferred.

· Proven track record and progressively responsible experience in data engineering, data architecture, or related technical roles; healthcare experience preferred

· Strong knowledge of data engineering principles, data integration, ETL processes, and semantic mapping techniques and best practices

· Experience implementing data quality management processes, data governance frameworks, cataloging, and master data management concepts.

· Familiarity with healthcare data standards (e.g., HL7, FHIR, etc), health information management principles, and regulatory requirements (e.g., HIPAA).

· Understanding of healthcare data, including clinical, operational, and financial data models, preferred.

· Advanced proficiency in SQL, data modeling, database design, optimization, and performance tuning.

· Experience designing and integrating data from disparate systems into harmonized data models or semantic layers.

· Handson experience with modern cloud-based data platforms (e.g Azure, AWS, GCP)

· Hands-on experience with data warehousing, data lakes, and analytics platforms (e.g., Microsoft Fabric, Snowflake, Redshift, BigQuery).

· Experience with Microsoft’s data ecosystem including Azure Data Factory, Azure SQL, Azure Data Lake, Microsoft Fabric, and Purview is highly desirable.

· Strong understanding of data security principles, including access controls, encryption, credential handling, and secure pipeline development.

· Experiencewith data visualization and analytics tools (e.g.,Tableau, Power BI) andstatistical analysis tools (e.g., R, Python).

· Demonstratedleadership and team management skills, with the ability to guide and mentordata engineers and analysts and foster technical excellence.

· Excellentanalytical, problem-solving, and debugging skills, with a keen attention to detail.

· Strongcommunication and stakeholder management skills, with the ability toeffectively convey complex technical concepts to non-technical audiences.

· Abilityto work in a fast-paced, dynamic environment and manage multiple prioritieseffectively.

· Resultsoriented self-starter with strong initiative, ownership mentality, and theability to manage commitments and deadlines independently.

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Benefits:
· Paid Time Off, Medical, Dental and Vision plans, Retirement plans

· Public Service Loan Forgiveness (PSLF)

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