The posting
Why Join the Pack? We understand that to win championships, it starts with the people. That’s why we’re all teammates with a united focus on fostering a winning culture that empowers, values and recognizes each other. Because working together is how we do what’s right for the communities we live, work and play in. It’s how we innovate, learn and grow as individuals and as a group. And it’s how we elevate lives through the power of basketball. Position Summary/Objective:The Data Engineering Manager owns data engineering and data strategy for the Minnesota Timberwolves and Lynx across ticketing, marketing, partnerships, sales, finance and operations, and architects and scales the unified data foundation behind them. The role owns data integrations, data infrastructure and automation workflows across CRM, ticketing, digital, mobile app, marketing automation and fan engagement platforms, and owns BI and Looker. It is central to the organization’s goal of leading in 1:1 marketing, predictive analytics and AI-enabled fan engagement, and works closely with the NBA and WNBA to keep data aligned with league standards. A hands-on player-coach, the role is as comfortable in a revenue strategy meeting as they are writing SQL, and leads and grows a team of data and analytics engineers.Essential Functions:Reasonable accommodations may be made to enable individuals to perform these essential functions. 1. Cross-functional, league and team leadership
Work directly with business stakeholders across Sales, Marketing, Partnerships, CRM, Technology and Finance to understand data needs, translate them into technical requirements and deliver solutions. Drive business strategy and measurable results through data. Work directly with NBA and WNBA data and technology teams, and represent the organization in league working groups on data standards and integrations. Plan and prioritize the team’s work through a regular, predictable delivery cadence, keeping work visible and tied to business priorities, while staying hands-on in the code. Own intake and prioritization of requests from every department. Lead, coach and develop the team’s engineers by setting technical direction, conducting code reviews, running regular 1:1s and owning hiring and performance management, and establish engineering standards and best practices.
2. AI enablement and API integration
Build and maintain secure API connections between our data systems and approved AI platforms. Structure pipelines to support AI-driven personalization, recommendation engines, scoring models and automation workflows. Monitor the performance, reliability and security of AI-related data integrations. Route AI-generated insights back into CRM, marketing automation, ticketing and other operational systems. Design, build and evolve the team’s own AI-enabled tech stack, including AI coding assistants, LLM integrations and automated agents, and pilot and scale AI in BSA workflows. Establish evaluation and governance standards for AI tools. Align AI work with the team’s broader initiatives and roadmap, prioritizing use cases with clear, measurable business value.
3. Business intelligence
Own BI and Looker, including governed metric definitions, semantic layer standards, documentation and self-serve content. Make sure dashboards give one trusted set of numbers that ties to Finance and league reporting. Support Finance’s month-end close with NetSuite, ticketing and revenue data that ties out. Drive adoption and usage of the modern data stack (Snowflake, Looker, Fivetran, dbt) across the organization, including training, office hours and a champions network.
4. Data integrity, governance and privacy
Establish and maintain data governance standards. Monitor and enforce data quality, accuracy and completeness across systems. Ensure compliance with privacy, consent management and league data policies. Serve as BSA’s counterpart to IT and Technology, partnering on data infrastructure, security and governance. Build validation checks, audit procedures and system monitoring dashboards, and track pipeline uptime and data freshness. Serve as the organization’s subject matter expert on data reliability and system health.
5. Automation and workflow enablement
Build and maintain the automated data workflows that power personalized 1:1 marketing journeys. With CRM and Marketing, enable campaign triggers, lead score writeback, lead distribution, renewal intent models and lifecycle orchestration. Make sure Sales and Marketing have the near-real-time data they need and that the data behind their automations is accurate and on time. Reduce manual reporting and data processing through scalable system design. Build the infrastructure for next-best-action and recommendation engines.
6. Enterprise data integration and architecture
Own data engineering and data strategy across the organization, including ticketing, marketing, partnerships, sales, finance and operations. Own and manage all data integrations across systems, including CRM, ticketing, marketing automation, mobile app, web, loyalty and partnerships.• Design, build and maintain scalable batch data pipelines, with near-real-time pipelines where the business case justifies it (e.g., lead routing, game day), and the unified CRM / data warehouse. Lead architecture decisions so the data ecosystem scales with the organization, optimizing for cost and performance. Own the data platform, including architecture, Snowflake administration (roles, warehouses and cost), the team’s footprint within IT’s Azure environment and platform vendors (e.g., Snowflake, Fivetran, Looker / Google Cloud), and evaluate and implement new data tools. Drive the data modernization initiative on the new data warehouse beyond its initial build, extending the platform into new use cases and departments. Oversee identity resolution and master data management to create a single view of each fan. Ensure league-required data integrations meet NBA and WNBA data standards.
This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time. Knowledge, Skills, Abilities and Other:
Expertise building ETL/ELT pipelines and scalable data workflows. Hands-on experience with modern data tools: Snowflake, Looker (or a similar BI platform), Fivetran (or similar ELT), dbt and cloud platforms (Azure preferred; AWS or GCP). Deep proficiency in SQL and Python. Snowflake administration (roles, warehouses and cost management) and cloud architecture experience. Working fluency with version control, code review and CI/CD practices. Daily use of AI coding assistants (e.g., Claude Code) and at least one LLM-backed workflow shipped to production. Strong data modeling skills, including dimensional modeling, semantic layers and governed metrics. Experience with data visualization, reporting and dashboard design. Experience integrating CRM (Dynamics 365 / Dataverse preferred), marketing automation and digital platforms. Experience implementing data governance and quality frameworks. Proven track record translating business problems into data solutions and driving measurable outcomes, working cross-functionally with non-technical stakeholders. Background spanning at least two of data engineering, analytics / BI and data science. Experience mentoring engineers and leading data or analytics projects, including setting technical direction; people management experience a plus. Experience running a lightweight delivery cadence, such as weekly triage and demos, planning every two weeks and tying every change to a tracked issue. 5+ years of experience in data engineering, analytics engineering or a related field.
Pay: $150,000-180,000 annually. Education: Bachelor’s degree in computer science, information systems, engineering or a related field, or equivalent experience. Specialized Knowledge, Licenses, etc.:Preferred: domain depth in marketing analytics, sales analytics or data engineering; experience in sports, entertainment or media; experience at a high-growth tech company or during a data platform migration or transformation; statistics, advanced analytics or predictive modeling; experience with league or enterprise-level data standards; experience putting machine learning models into production; experience with vector databases and AI agents; familiarity with real-time streaming technologies; exposure to customer data platforms, identity resolution and customer journey orchestration platforms. Supervisory Responsibility: This position manages a team of data and analytics engineers. Work EnvironmentThis job operates in a professional office environment. Office hours are typically 8:00 AM-5:00PM Monday-Friday. In addition to working office hours staff may work Timberwolves and Lynx home games as well as external events including but not limited to: charity and networking events. Work is both sedentary and active in nature. The working environment is generally favorable. Office lighting and temperature are adequate, and there are no hazardous or unpleasant conditions caused by noise, dust, etc. Work is generally performed within an office environment, with standard office equipment available, and may also operate in a sports arena which includes bleachers/steps and moderate noise levels. Physical DemandsThe physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. While performing the duties of this job, the employee is regularly required to communicate and exchange information with others both in person and over the telephone. The employee frequently is required to remain in a stationary position, as well as operate computers and other office equipment, such as a copy machine, printer and telephone. Staff may occasionally ascend and descend bleachers/steps and traverse around the arena both on event days and non-event days. Staff may occasionally move boxes or other items weighing up to 15 pounds. TravelPosition may require travel. EEO StatementThe Minnesota Timberwolves and Lynx are an equal employment opportunity organization. E-Verify StatementWe participate in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot prove this, we will give you written instructions and an opportunity to contact Department of Homeland Security (DHS) or Social Security Administration (SSA) to resolve the issue before any action might be taken against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.
