Sr. Director, Data Services

Blue Shield of CaliforniaOakland, CA
2dHybrid

About The Position

As Senior Director, Data Services, you will be responsible for leading the enterprise data foundation that powers analytics, AI, and digital solutions across Stellarus. Reporting to the SVP/CTO, you will play a key role in advancing a data- and AI-driven organization. You will own the enterprise data platform and engineering ecosystem, overseeing ingestion, transformation, storage, governance, and delivery. Your leadership enables trusted reporting, advanced analytics, and AI/ML solutions for analysts, data scientists, applications, and partners. You will lead multiple data services teams, manage partner portfolios, and collaborate with leaders in Application Development, Security, Infrastructure, and Analytics. Success requires strong technical expertise, hands-on experience with data engineering pipelines and AI integration, executive presence, and the ability to build high-performing teams that deliver results at scale. We seek a leader passionate about modern data platforms, innovation, operational excellence, and continuous learning who can translate strategy into action. Our leadership model is about developing great leaders at all levels and creating opportunities for our people to grow – personally, professionally, and financially. We are looking for leaders that are energized by creative and critical thinking, building and sustaining high-performing teams, getting results the right way, and fostering continuous learning.

Requirements

  • Requires a bachelor's degree or equivalent experience; advanced degree preferred
  • Requires a minimum of 12 years of experience in data engineering, AI based development, data management, and data platform leadership within large, complex environments, including 6 years of management experience
  • Proven experience designing and operating modern AI driven cloud data platforms (Azure preferred) and cloud data warehouses (Snowflake preferred)
  • Hands on experience with data modelling, data integration (ELT using DBT or other tools) and engineering certified data products
  • Deep understanding of enterprise data management concepts including metadata management, data quality, governance, Mastering Data, and analytics enablement with semantic and facts and dimensional models
  • Demonstrated ability to modernize or build data platforms from the ground up
  • Experience enabling analytics AI use cases at scale
  • Strong people leadership skills with a track record of building and leading multi‑disciplinary teams
  • Exceptional communication skills with the ability to influence and align stakeholders from engineers to senior executives
  • Strong business acumen and ability to align technical decisions with enterprise strategy and outcomes
  • Experience operating in agile and product‑centric delivery models
  • Highly organized, resilient, and energized by complex challenges

Responsibilities

  • Own and evolve the enterprise data platform across Azure, Snowflake, ensuring scalability, reliability, security, and cost efficiency aligned with business strategy
  • Serve as the single accountable owner of enterprise data assets, defining data domains, layers, ownership models, and data contracts that enable trusted, reusable data at scale
  • Lead modern data engineering practices (ELT, modular pipelines, CI/CD, version control) to deliver high‑quality data for analytics, applications, APIs, and AI use cases
  • Establish and enforce data quality, governance, and trust frameworks, including data definitions, quality rules, lineage, catalogs, SLAs, and observability, in partnership with Security, Privacy, and Compliance
  • Enable AI‑driven analytics and automation by ensuring data is discoverable, well‑modeled, governed, and optimized for feature engineering, experimentation, and operationalization
  • Own and optimize the data tools and platform portfolio, continuously modernizing and rationalizing tooling to improve developer productivity, self‑service, and organizational throughput
  • Lead, develop, and retain high‑performing teams across data engineering, modeling, platform operations, and governance, fostering a culture of accountability and continuous learning
  • Manage strategic partnerships and external partners, balancing speed, quality, and cost while maintaining architectural standards and growing internal capabilities
  • Partner with executive and technology peers to translate business strategy into a clear data and AI roadmap that accelerates insights, digital products, and enterprise transformation
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