Lead Data Engineer

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

Requirements

• 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.
• Company:
• OC Sports & Entertainment, LLC
• Our Commitment:
• Thanks for your interest in becoming part of OCVIBE!

Benefits

Additional Information

A great experience starts with you! Join our team to help create and develop the future of live entertainment and sports in Orange County! Once you've had a chance to explore our current open positions, apply to the ones you feel best suit you, as an applicant, you can always see your application status in your profile. Mission: To enrich the lives in our community through shared experiences, welcoming spaces, and responsible actions. Vision: We will be the social and entertainment center of Orange County - a place where the cultural kaleidoscope of the region converges and connects. Our vibrant, rich collection of experiences will celebrate the diversity of our community. Values: Be Safe | Do the Right Thing | Be Generous | Include Everyone | Make it Easy | Be Bold Job Title: Lead Data Engineer Pay Details: The annual base salary range for this position in California is $140,000 to $180,000 per year. The starting pay for the successful candidate depends on various job-related factors, including but not limited to the candidate's geographic location, job-related knowledge, skills, experience, education/training, internal value, peer equity, external market demands, and organizational considerations. 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.

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