Data Engineering & Analytics Lead Jobs

Premium Health

Location:
United States, Brooklyn

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

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.

Job Responsibility:

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
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
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
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
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
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
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

Requirements:

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred
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
Hands-on 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
Experience with data visualization and analytics tools (e.g.,Tableau, Power BI) and statistical analysis tools (e.g., R, Python)
Demonstrated leadership and team management skills, with the ability to guide and mentor data engineers and analysts and foster technical excellence
Excellent analytical, problem-solving, and debugging skills, with a keen attention to detail
Strong communication and stakeholder management skills, with the ability to effectively convey complex technical concepts to non-technical audiences
Ability to work in a fast-paced, dynamic environment and manage multiple priorities effectively
Results oriented self-starter with strong initiative, ownership mentality, and the ability to manage commitments and deadlines independently

What we offer:

Paid Time Off, Medical, Dental and Vision plans, Retirement plans
Public Service Loan Forgiveness (PSLF)

Additional Information:

Job Posted:
December 11, 2025

Employment Type:

Fulltime

Work Type:

Hybrid work

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Data Engineering & Analytics Lead