Data Engineer Manager

Data Architecture and Pipeline ManagementDesigns 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 and DevelopmentRecruits, 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 and Requirements GatheringWorks 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 and ComplianceEnsures 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 and InnovationContributes 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 and Resource ManagementManages the data engineering teams 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/AbilitiesManages ComplexityBreaks down ambiguous problems into manageable components.Uses multiple data sources to inform decisions.Designs scalable solutions for evolving data needs.Tech SavvyEvaluates and integrates new tools (e.g., cloud platforms).Encourages experimentation and innovation.Maintains fluency in modern data engineering stacks.CollaboratesFacilitates cross-functional meetings.Resolves conflicts constructively.Shares credit and fosters team cohesion.Plans and AlignsDevelops clear project plans and milestones.Communicates expectations effectively.Ad usts plans based on feedback and performance.Ensures AccountabilityTracks progress and outcomes.Provides timely feedback.Establishes clear roles and responsibilities.Strategic MindsetAnticipates future data needs.Aligns technical decisions with business strategy.Identifies long-term opportunities for data innovation.