Data Engineer Manager Full-time

Data Engineer Manager

The Data Engineer Manager leads a team of data engineers responsible for designing, building, and maintaining scalable data infrastructure and pipelines that support clinical, operational, and financial analytics across the healthcare system. This role collaborates closely with data scientists, software engineers, business intelligence analysts, and clinical informatics teams to ensure data is accessible, accurate, and secure. Reporting to the Director of Data Systems and Analytics, the position plays a critical role in enabling data-driven decision-making and innovation in a complex healthcare environment.

Responsibilities

Data Architecture & Pipeline Management

• Designs and oversees scalable data pipelines for structured and unstructured data across clinical, operational, and financial systems.
• Manages ETL/ELT processes using tools such as Apache Spark, Kafka, Airflow, and other modern orchestration platforms.
• Ensures data integrity, availability, and performance across cloud and on-premise platforms.
• Implements and maintains data lake and warehouse solutions (e.g., Snowflake, BigQuery, Redshift).
• Collaborates with infrastructure and application teams to optimize data flow and storage.

Team Leadership & Development

• Recruits, mentors, and manages a team of data engineers, fostering a high-performance and inclusive team culture.
• Conducts performance evaluations, sets development goals, and supports career progression.
• Promotes collaboration, innovation, and continuous learning through team meetings, code reviews, and knowledge-sharing sessions.
• Aligns team goals with organizational priorities and strategic initiatives.
• Ensures adherence to engineering best practices and coding standards.

Stakeholder Collaboration & Requirements Gathering

• Works closely with clinical, operational, and financial stakeholders to define data needs and translate business requirements into technical specifications.
• Facilitates cross-functional communication between IT, analytics, clinical informatics, and business intelligence teams.
• Leads discovery sessions and data mapping exercises to ensure alignment between data engineering deliverables and business objectives.
• Supports the development of dashboards, reports, and predictive models by enabling access to clean, well-structured data.

Data Governance & Compliance

• Ensures adherence to HIPAA, HITECH, and internal data governance policies, including data privacy and security protocols.
• Implements data security measures, access controls, and encryption standards across all data platforms.
• Supports audit readiness and regulatory reporting by maintaining accurate metadata and lineage documentation.
• Collaborates with data governance and compliance teams to establish and enforce data quality standards.

Strategic Planning & Innovation

• Contributes to the development and execution of the enterprise data strategy and roadmap.
• Evaluates emerging technologies and recommends adoption to improve scalability, performance, and cost-efficiency.
• Aligns data engineering initiatives with strategic goals of the healthcare system, including population health, value-based care, and operational excellence.
• Participates in long-term planning for data infrastructure modernization and cloud migration.

Budget & Resource Management

• Manages the data engineering team's operational budget, including software licenses, cloud services, training, and professional development.
• Tracks resource utilization and optimizes operational efficiency through capacity planning and workload balancing.
• Supports vendor selection, contract negotiations, and license renewals for data platforms and tools.
• Provides input into capital planning and technology investment decisions.

Marginal or Periodic Functions:

• Participates in enterprise-wide data governance committees.
• Presents at internal and external conferences or forums.
• Assists in grant writing or research data infrastructure proposals.
• Conducts periodic system performance audits.
• Adheres to internal controls and reporting structure.
• Performs related duties as required.

Knowledge/Skills/Abilities

Manages Complexity

• Breaks down ambiguous problems into manageable components.
• Uses multiple data sources to inform decisions.
• Designs scalable solutions for evolving data needs.

Tech Savvy

• Evaluates and integrates new tools (e.g., cloud platforms).
• Encourages experimentation and innovation.
• Maintains fluency in modern data engineering stacks.

Collaborates

• Facilitates cross-functional meetings.
• Resolves conflicts constructively.
• Shares credit and fosters team cohesion.

Plans and Aligns

• Develops clear project plans and milestones.
• Communicates expectations effectively.
• Adjusts plans based on feedback and performance.

Ensures Accountability

• Tracks progress and outcomes.
• Provides timely feedback.
• Establishes clear roles and responsibilities.

Strategic Mindset

• Anticipates future data needs.
• Aligns technical decisions with business strategy.
• Identifies long-term opportunities for data innovation.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, or related field. 10 years of experience in data engineering or data architecture including designing data architectures, developing data pipelines, implementing data quality, and performance monitoring. 2 years of experience in a technical leadership or team lead role with a track record of delivering complex data projects and mentoring junior engineers in a fast-paced department. Experience in healthcare data systems (e.g., EHR, claims, HL7, FHIR). Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

Master's degree in Data Science, Engineering, or Healthcare Informatics. 7+ years of progressive experience in data engineering. Experience with cloud platforms (e.g., GCP, AWS, Azure).

Salary Range

$135,000+ depending on qualifications

Working Conditions

Standard office conditions.

Required Materials

• Resume/CV
• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest