Data Engineer

The Los Angeles Sparks are seeking a Data Engineer to lead the design and evolution of the team’s basketball data infrastructure. This role will help us build & maintain objective information across scouting, coaching, player development, performance, and strategy. As a member of the Research & Development group, you will own core systems, mentor analysts and junior engineers, and partner directly with different data stakeholders across Basketball Operations.

This position reports to the Assistant General Manager, Research & Development.

Data Infrastructure & Architecture

Lead the design, implementation, and maintenance of scalable data pipelines that ingest, transform, and deliver basketball data.

• Build and manage the Sparks’ database, ensuring reliability, performance, and security
• Develop internal data that support analytics for player evaluation, coaching, scouting, performance, and salary cap/roster planning
• Implement automated data QC/QA, and monitoring systems

Data Integrations & Technology

Oversee integrations with major basketball data providers (e.g., Second Spectrum, Synergy Sports, WNBA/official league feeds).

• Design internal data feeds, tools, and services used by executives, analysts, coaches, and performance staff

Collaboration & Leadership

• Serve as the technical lead for engineering within Basketball Operations
• Partner with analysts to translate analytical needs into robust, scalable engineering solutions
• Guide our Research & Development growth while balancing quick data delivery and future-focused data engineering practices
• Work closely with coaching, scouting, and performance teams to deliver data that improves preparation, decision-making, and player development
• Provide mentorship and guidance to teammates on best practices in data engineering

KNOWLEDGE,

SKILLS AND ABILITIES

Ability to design and maintain production-grade pipelines supporting analytics.

• Ability to work flexibly during the WNBA season including evenings, weekends and holidays
• Prior experience building data workflows for basketball or other sports analytics teams
• Familiarity with player tracking data, advanced play-by-play feeds, and sports science/wearable data
• Experience supporting data needs for coaching, scouting, and high-performance departments
• Understanding of basic statistical and modeling concepts used in basketball analytics
• Passion for innovation in women’s basketball

MINIMUM REQUIREMENTS

Education & Certification:
Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related technical field preferred.

Experience:

3+ years of professional experience in data engineering or backend/data infrastructure roles.

• Expert-level proficiency in SQL
• Strong R and/or Python development skills
• Experience with modern databases
• Strong understanding of ETL/ELT patterns, data modeling, and distributed data systems
• Demonstrated experience with cloud platforms (AWS, GCP, or Azure)
• Experience with orchestration/workflow tools (Airflow, Dagster, Prefect)

Compensation commensurate with experience; minimum starting salary $125,000

This job description in no way states or implies that these are the only duties to be performed by the employee in this position. It is not intended to give all the details or a step-by-step account of the way each procedure or task is performed. The incumbent is expected to perform other duties necessary for the effective operation of the department.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, age, disability, gender identity, marital or veteran status, or any other protected class.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform critical job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.