Data Operations Engineer

Before we get into the specifics of the role, there are a few things we want you to know:

At the Orlando Magic, our approach is to not only learn as much about you as we can, but for you to learn about us. This is definitely a two-way street, so time with your potential new leader, teammates, and/or other departments that the role will work with is critical. It isn’t just, “what are we looking for”, but also, “what do we have to offer you” and “are we the right fit for you.”

While every position is different, our interview process is typically a three-step process, sometimes more depending on the level and nature of the role.

• 18 days of personal time off per year + 13 holidays (that is 31 paid days off year!) plus reduced summer work hours (every other Friday off during the off-season, which averages to another 8 days)
• A hybrid work model, casual work attire on non-game days, staff tickets to Magic home games, learning and development opportunities, Employee Resource Groups (ERGs), company sponsored events, volunteer opportunities & outings for every employee
• Fantastic benefits that include: medical, dental, vision, 401(k) with company matching, mental wellness resources, subsidized gym memberships, maternity & paternity leave
• Culture built on Community, Innovation, Legendary and Teamwork!

The Data Engineering & Cloud Architecture group owns and operates the organization’s data warehouse, business and basketball analytics platforms, and CRM ecosystem to drive performance, innovation, and long-term growth.

The Data Operations Engineer is responsible for the reliability, scalability, and operational excellence of the organization’s data platforms and analytics products. This role sits at the intersection of data engineering and analytics, ensuring that data pipelines, dashboards, models, and AI-driven solutions are production-ready, well-governed, and continuously monitored.

Partnering closely with BI engineering, analytics, and other business and basketball stakeholders, the Data Operations Engineer designs and maintains robust data workflows, implements data quality and observability frameworks, and manages deployment processes across modern cloud-based infrastructure. This role also supports API integrations, model deployment, and emerging capabilities such as embedded analytics, A.I. systems, and privacy-safe data collaboration environments.

With a strong focus on automation, testing, documentation, and system optimization, the Data Operations Engineer drives continuous improvement in data platform performance, cost efficiency, and operational maturity. This position plays a key role in establishing best practices across data governance, security, and analytics operations, while supporting internal platforms and ensuring seamless delivery of trusted data to stakeholders across the organization.

• Own and maintain data operations workflows, ensuring analytics products, dashboards, and models are reliable, performant, and production‑ready
• Develop and maintain data quality monitoring, dashboards, and alerting systems to proactively identify issues across core datasets and pipelines
• Design, deploy, and operate production‑grade data services and pipelines, including CI/CD automation (e.g., Git Hub Actions), containerization (Docker), and cloud orchestration (e.g., AWS ECS)
• Establish and maintain logging, monitoring, and observability standards for data systems (e.g., pipeline health, latency, and failures)
• Develop automated testing frameworks for data pipelines, including unit, integration, and regression testing
• Partner with BI Engineering and Analytics teams on documentation, QA processes, and release coordination for new and existing data products
• Support model deployment and AI implementations, including BI chatbots and embedded analytics, ensuring proper validation, monitoring, and operational handoff
• Manage and support API integrations, including troubleshooting data ingestion, delivery, and downstream consumer issues
• Assist in the implementation and ongoing operation of data clean rooms and…