Lead Data Engineer at OC Sports & Entertainment
Lead Data Engineer
OC Sports & Entertainment
Anaheim, CA
Full-time
Salary not listed
Posted 17 July 2026
EngineeringMid-level
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Job Description
The Lead Data Engineer is responsible for designing, building, and governing a reliable data warehouse architecture that unifies key business data across ticketing, loyalty, and F&B systems. This role owns critical data engineering standards, identity resolution, Azure environment governance, and production-grade pipeline development while partnering with business and technical stakeholders to deliver trusted data products that support analytics, operations, and decision-making.
Responsibilities
- Design and build a governed data warehouse architecture that unifies ticketing, loyalty, and F&B data into a single trusted source of truth
- Own identity resolution end-to-end, including defining the entity framework, setting coverage standards, and expanding capabilities as new source systems are onboarded
- Govern the Azure data environment, including monitoring, alerting, cost controls, and consolidation into a single reliable warehouse
- Serve as the internal technical counterpart to the implementation partner by auditing the existing platform, evaluating architectural decisions, and driving toward full internal ownership
- Translate complex data architecture decisions for non-technical business partners and collaborate with analytics and operations teams to deliver data products that drive business decisions
- Mentor engineers and help build a culture of technical rigor while remaining hands-on as a builder
Qualifications
- 6–9 years of hands-on data engineering experience designing and building production-grade systems
- Academic background in a quantitative or technical field such as physics, mathematics, computer science, engineering, or a related field
- Production-grade pipeline development experience in Python and advanced SQL, with strong attention to performance, observability, and maintainability
- Production experience with dbt, including project structure, robust test coverage, and development of reliable transformation layers that support downstream reporting and analytics
- Production experience with Airflow or equivalent tools, such as Dagster or Prefect, including DAG design, dependency management, and failure handling at scale
- Deep cloud data warehouse experience; Azure preferred, with strong AWS or GCP experience transferable
- Experience building or enforcing medallion architecture in a production environment
- Experience inheriting or auditing an externally managed platform, including reviewing unfamiliar codebases and independently evaluating architectural decisions
- Experience owning engineering standards, including code review, pipeline governance, and documentation practices
- AI-native mindset, with experience using AI-assisted tools as a productivity multiplier
Knowledge, Skills, and Experience
Education -
Bachelor's Degree
Experience Required –
6\+ Years
This position is on-site.