Vice President, Data Systems

The Los Angeles Lakers, Inc•El Segundo, CA

4d•$275,000 - $300,000•Onsite

About The Position

The Vice President, Data Systems provides strategic and technical leadership for the organization’s data, software engineering, and technology infrastructure. The role oversees the design, development, and continuous improvement of enterprise data platforms, applications, and systems, and establishes the technical vision, architecture, and engineering standards for collecting, integrating, managing, and delivering data across basketball operations, analytics, performance, medical, and business functions. The position drives technology strategy, data governance, system reliability, and product innovation, ensuring solutions are secure, scalable, and aligned with organizational priorities. It also leads and develops a multidisciplinary engineering and product team, fostering innovation, collaboration, operational excellence, and continuous improvement. The role owns the organization’s cloud data platform architecture, including data ingestion, transformation, storage, and serving, and supports the development of modern production-grade infrastructure and curated, validated datasets. It leads the development and delivery of internal web and mobile applications, product management, and shared data models, APIs, and service layers across departments. The Vice President establishes engineering and operational practices, service-level expectations, data security and governance standards, and a long-term technology roadmap. Responsibilities also include managing technology budgets, vendor contracts, cloud spending, and recruiting, developing, and managing a multidisciplinary technical team. The position is based in El Segundo, with offices Monday through Friday, occasional off-site events, and attendance at Lakers home games at Crypto.com Arena when necessary. Travel is less than 10% of the time. Regular hours are 9:00 a.m. to 5:30 p.m., Monday through Friday. The annual pay range is $275,000–$300,000; actual compensation depends on candidate-specific factors and internal pay considerations.

Requirements

Bachelor’s degree in computer science, software engineering, data science, information systems, or a related technical discipline.
Significant progressive experience leading data engineering, software development, and enterprise technology initiatives, including managing multidisciplinary technical teams.
At least 10 years of relevant professional experience, including at least five years in a technical leadership or management capacity.
Deep understanding of modern data architecture, data engineering principles, cloud-based data platforms, and enterprise technology infrastructure.
Experience with AWS, Azure, or Google Cloud and modern data warehousing.
Strong knowledge of data integration, ETL/ELT pipelines, orchestration, APIs, data modeling, and data governance frameworks.
Experience overseeing software engineering and application development, including web and mobile applications, full-stack development, and product lifecycle management.
Familiarity with programming languages and frameworks such as Python, SQL, and JavaScript/TypeScript, and related development technologies.
Knowledge of data security, privacy, access controls, encryption, and compliance practices, particularly for sensitive employee, athlete, medical, and organizational data.
Ability to translate complex technical concepts into practical solutions that support organizational strategy and end-user needs.

Nice To Haves

Master’s degree in computer science, data engineering, or a related field.

Responsibilities

Set the technical vision and engineering standards for data engineering, web and mobile development, and platform infrastructure.
Ensure systems and overall architecture are reliable, scalable, secure, and serve coaches, front office, scouts, medical and performance staff, and players.
Own the end-to-end architecture of the organization’s cloud data platform, including ingestion, transformation, storage, and serving layers.
Support and direct the transition to modern, production-grade data infrastructure and provide analysts and modelers with curated, validated, development-ready datasets.
Lead the design, development, and delivery of internal web and mobile applications that deliver data and model outputs to decision makers.
Oversee product management across the organization, translating user needs into prioritized roadmaps, intuitive interfaces, and production-caliber releases.
Ensure applications address usability, accessibility, offline and travel use, and adoption across departments.
Build shared data models, APIs, and service layers to integrate Performance Strategy, Analytics Strategy, and Cap Strategy divisions and avoid duplicated effort.
Establish consistent and reliable sources of truth across the organization.
Set and enforce software and data engineering best practices, including version control, code review, CI/CD, infrastructure-as-code, automated testing, observability, and incident response.
Establish service-level expectations for uptime, latency, and data freshness, particularly during time-sensitive periods such as gameday, draft, and trade deadline.
Set standards for data access, permissions, encryption, retention, and audit trails, and ensure sensitive data complies with NBA, CBA, and organizational security and privacy requirements.
Oversee data validation frameworks, schema enforcement, and automated quality monitoring.
Own the long-term roadmap for data and software infrastructure, including build-versus-buy decisions, vendor and feed provider evaluation, cloud storage and compute strategy, and emerging tools.
Manage the division’s technology budget, vendor contracts, and cloud spend, considering interoperability, security, return on investment, and emerging technologies.
Recruit, develop, and manage data engineers, developers, full-stack engineers, product and design staff, and platform/DevOps engineers.
Set team goals, define career ladders and technical growth paths, mentor staff, and foster ownership, documentation, and close collaboration with analysts and end users.
Perform other responsibilities as organizational needs and management direction require.