Senior Manager, Data Engineering

Stanford Health Care • Palo Alto, CA

1d • $84 - $111

About The Position

Stanford Health Care is seeking a dynamic and experienced Senior Manager of Data Engineering to lead our data engineering teams. This role is critical to our mission of leveraging data to drive clinical innovation, operational efficiency, enterprise analytics, and groundbreaking research across Stanford Medicine. This is a Stanford Health Care job. Stanford Health Care is seeking a dynamic and experienced Senior Manager of Data Engineering to lead our data engineering teams. This role is critical to our mission of leveraging data to drive clinical innovation, operational efficiency, enterprise analytics, and groundbreaking research across Stanford Medicine. The ideal candidate will be a strategic leader with deep technical expertise who can manage multiple technical teams. You will be responsible for the teams that design, build, and maintain our enterprise data pipelines and platforms, and for partnering with stakeholders to deliver enterprise analytics and operational reporting solutions. This position requires close collaboration with clinical, operational, and research leaders to implement a cohesive strategy for data management, analytics, and governance.

Requirements

• Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field. A Master’s degree is preferred.
• Experience: 8+ years of hands-on experience in data engineering, data warehousing, or a related field. 3+ years of experience in a leadership or management role, directly managing multiple technical teams.
• Proven ability to lead, mentor, and grow multiple high-performing engineering teams.
• Expert knowledge of data engineering principles, including ETL/ELT, data modeling, and data architecture.
• Strong strategic planning skills with experience in developing roadmaps for both data engineering and enterprise analytics.
• Deep understanding of cloud data platforms (GCP, AWS, Azure) and modern data warehouse technologies (Databricks, Snowflake, BigQuery, Redshift).
• Proficiency with big data technologies (e.g., Spark, Kafka) and workflow orchestration tools (e.g., Airflow).
• Expert-level SQL skills and proficiency in a programming language such as Python or Scala.
• Excellent communication, strategic thinking, and stakeholder management skills across a complex, multi-entity organization.
• Strong understanding of data security best practices, data governance frameworks, and regulatory requirements, particularly HIPAA

Nice To Haves

• Experience in a healthcare or academic medical center environment is highly desirable.

Responsibilities

• Team Leadership and Development: Lead, mentor, and manage multiple teams of data engineers, providing technical guidance, career development, and performance management. Foster a culture of collaboration, innovation, and operational excellence. Manage resource allocation, project prioritization, and team workloads to ensure timely delivery of key initiatives. Recruit, coach, and motivate team members, developing leadership competencies within the team.
• Strategy, Architecture, and Analytics: Oversee the design, development, and maintenance of scalable and robust data pipelines (ETL/ELT) to support analytics and data science. Define and drive the technical roadmap for our cloud-based data platforms (e.g., GCP, AWS, Azure) and data warehousing solutions (e.g., Databricks). Define and implement the strategy for enterprise analytics and operational reporting, in collaboration with key business and clinical stakeholders. Partner with enterprise architecture, applications, and data science teams to ensure sustainable and scalable data management and solution delivery.
• Stakeholder Collaboration and Project Management: Partner with key stakeholders across Stanford Medicine (Stanford Health Care, Stanford School of Medicine, and Stanford Medicine Partners), including data scientists, analysts, clinical leaders, and researchers, to translate data needs into technical requirements. Manage the full lifecycle of data engineering projects, from conception and planning to execution and delivery. Deploy and facilitate robust project and data governance processes to ensure alignment with enterprise standards. Communicate project status, risks, and outcomes to senior leadership.
• Governance and Operational Excellence: Ensure the integrity, reliability, and performance of all data platforms and pipelines. Implement and enforce data governance policies and security protocols to protect sensitive patient information and ensure compliance with HIPAA. Establish and support an organizational structure that enables effective enterprise reporting and data management. Develop and manage the operational budget for the data engineering teams and associated cloud services.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager