Job description

If you re ready to be part of our legacy of hope and innovation, we encourage you to take the first step and explore our current job openings. Your best is waiting to be discovered. Day - 08 Hour (United States of America) 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. Essential Functions: 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. Minimum Qualifications: 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. Experience in a healthcare or academic medical center environment is highly desirable. Knowledge, Skills, and Abilities: 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 These principles apply to ALL employees: SHC Commitment to Providing an Exceptional Patient & Family Experience Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford’s patient-experience and represents a framework for patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery. You will do this by executing against our three experience pillars, from the patient and family’s perspective: Know Me: Anticipate my needs and status to deliver effective care Show Me the Way: Guide and prompt my actions to arrive at better outcomes and better health Coordinate for Me: Own the complexity of my care through coordination Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements. Base Pay Scale: Generally starting at $83.98 - $111.27 per hour The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.

Requirements

Must-haves

If you re ready to be part of our legacy of hope and innovation, we encourage you to take the first step and explore our current job openings. Your best is waiting to be discovered.
Day - 08 Hour (United States of America)
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.
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.
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.
Experience in a healthcare or academic medical center environment is highly desirable.
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.

Nice-to-haves

Education: Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field. A Master’s degree is preferred.

Application prep

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Keywords to mirror

gcpawsazuresqlpython

Platform: workday
Effort: long