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. What we offer you: 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! A quick summary about the Data Operations Engineer role: 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. What the Data Operations Engineer will do: 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., GitHub 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 privacy‑safe data collaboration initiatives Implement and maintain data access controls, secrets management, and secure data handling practices Optimize data warehouse performance, compute spend, and system utilization, providing actionable reporting and recommendations Own administration of Magic Insights and other automated reporting management, including configuration, monitoring, and stakeholder support Administer and support internal platforms such as the in‑house App Badge CMS, ensuring data accuracy, access controls, and system reliability Collaborate with cross‑functional partners to improve data governance, operational standards, and analytics best practices across the organization Create and maintain technical documentation for pipelines, systems, and operational processes Drive continuous improvement of data platform reliability and operational maturity All other duties as assigned. What the Data Operations Engineer needs to have: College degree requirement: 4-year degree in Computer Science, Data Analytics, Information Systems or equivalent work experience and three+ (3+) years supporting data production, analytics, or BI platforms in a data operations, data engineering, or analytics engineering role preferred. Strong analytical and problem‑solving skills, with the ability to translate technical issues into clear business impact required. Working knowledge of analytics engineering tools or patterns (e.g., dbt, semantic layers, metrics governance) Hands‑on experience using Python, or similar, to support data workflows, automation, validation, or operational tooling required. Strong working experience with Snowflake, including querying, performance optimization, and supporting analytics workloads preferred. Experience working in AWS environments, including familiarity with cloud storage, compute, and data integration patterns preferred. Demonstrated ability to monitor, troubleshoot, and resolve data quality, pipeline, or API issues in a production environment preferred. Experience collaborating with BI, analytics, and engineering teams on documentation, QA, and release processes preferred. Familiarity with data quality frameworks, monitoring dashboards, and alerting systems. Experience supporting or deploying machine learning models, AI tools, or embedded analytics in production environments. Exposure to data clean rooms, privacy‑safe data sharing, or governed external data collaborations. Comfort working in Agile or cross‑functional team environments, balancing multiple initiatives and operational priorities. Willingness to work a flexible schedule including nights and weekends and be on‑call as necessary based on the changing priorities of the department. Proficient in all Microsoft Office products and other related computer skills required. Ability to meet tight deadlines and work well under pressure. Strong organizational skills, time management skills and attention to detail required. Strong verbal and written communication skills with an emphasis on business writing skills. Ability to prioritize and manage multiple tasks/projects. Ability to work independently without supervision, be self‑directed and demonstrate initiative. Ability to work half Magic home games (20). This includes the ability to work a flexible schedule including nights and weekends and be on‑call as necessary based on the changing priorities of the department. Physical requirements None If thisopportunity is a role you're passionate about and it fits with your skills and experience, then we welcome you to take the next step and apply! All offers of employment are contingent upon successful completion of our pre‑employment screenings, that will include a background check and may include a drug screen. Please note that this is not necessarily an exhaustive list of all responsibilities, duties, skills, efforts, requirements or working conditions associated with the job. While this is intended to be an accurate reflection of the current job, management reserves the right to revise the job or to require that other or different tasks be performed as assigned. The Orlando Magic are not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at the Orlando Magic via‑email, the internet or in any form and/or method without a valid written Statement of Work in place for this position from Orlando Magic HR/Recruitment will be deemed the sole property of the Orlando Magic. No fee will be paid in the event the candidate is hired by the Orlando Magic as a result of the referral or through other means. The Orlando Magic is an Equal Opportunity Employer that does not discriminate on the basis of actual or perceived race, religion, color, sex (including pregnancy and gender identity), sexual orientation, parental status, national origin, age, disability, family medical history or genetic information, political affiliation, military service, any other non‑merit based factor or any other characteristic protected by applicable federal, state or local laws. Our leadership team is dedicated to this policy with respect to recruitment, hiring, placement, promotion, transfer, training, compensation, benefits, employee activities and general treatment during employment. If you’d like more information about your EEO rights as an applicant under the law, please visit Equal Opportunity Employer This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor. #J-18808-Ljbffr