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Senior Manager, Data Engineering

San Francisco

SpringCube

Full-time - Engineering Manager

Healthcare Services & Tech

Posted 4 weeks ago

Disclosed upon interview

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Job Description

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Company Overview

A leading healthcare organization is seeking an experienced Senior Manager, Data Engineering to lead multiple data engineering teams and support enterprise-wide initiatives involving clinical innovation, operational efficiency, enterprise analytics, and research.

The organization is focused on leveraging modern data platforms and engineering capabilities to strengthen data management, analytics, reporting, and governance across a complex healthcare and academic environment.

Essential Functions

Team Leadership and Development

  • Lead, mentor, and manage multiple teams of data engineers while 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 while developing leadership capabilities across the organization.

Strategy, Architecture, and Analytics

  • Oversee the design, development, and maintenance of scalable and reliable data pipelines using ETL/ELT processes to support analytics and data science.
  • Define and drive technical roadmaps for cloud-based data platforms, including GCP, AWS, and Azure.
  • Oversee modern data warehousing solutions such as Databricks and other enterprise data technologies.
  • Define and implement strategies for enterprise analytics and operational reporting in collaboration with 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

  • Collaborate with data scientists, analysts, clinical leaders, researchers, and other stakeholders to translate data requirements into effective technical solutions.
  • Manage the full lifecycle of data engineering projects, from conception and planning through execution and delivery.
  • Establish and facilitate robust project and data governance processes aligned with enterprise standards.
  • Communicate project status, risks, challenges, and outcomes to senior leadership.

Governance and Operational Excellence

  • Ensure the integrity, reliability, availability, and performance of enterprise data platforms and pipelines.
  • Implement and enforce data governance policies and security protocols designed to protect sensitive patient information.
  • Ensure data engineering practices support applicable healthcare privacy and compliance requirements, including HIPAA.
  • Establish organizational structures that enable effective enterprise reporting and data management.
  • Develop and manage operational budgets for data engineering teams and associated cloud services.

Minimum Qualifications

  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
  • Master’s degree is preferred.
  • 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 within a healthcare or academic medical center environment is highly desirable.

Knowledge, Skills, and Abilities

  • Proven ability to lead, mentor, and develop multiple high-performing engineering teams.
  • Expert knowledge of data engineering principles, including ETL/ELT, data modeling, and data architecture.
  • Strong strategic planning capabilities with experience developing roadmaps for data engineering and enterprise analytics.
  • Deep understanding of cloud data platforms, including GCP, AWS, and Azure.
  • Strong knowledge of modern data warehouse technologies such as Databricks, Snowflake, BigQuery, and Redshift.
  • Proficiency with big data technologies such as Spark and Kafka.
  • Experience with workflow orchestration tools such as Airflow.
  • Expert-level SQL skills.
  • Proficiency in a programming language such as Python or Scala.
  • Excellent communication, strategic thinking, and stakeholder management skills.
  • Ability to collaborate effectively across a complex, multi-entity organization.

Disclaimer

SpringCube curates tech job listings from various company websites to support tech professionals globally.

  1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
  2. No Client Relationship: This company is not a client of SpringCube unless stated.
  3. To Apply: Click the Apply button to be redirected to the hiring company’s application page for this job.
  4. No Liability: SpringCube is not liable for inaccuracies.
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