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US - Florida, United States of America
Remote only
JOIN THE BEST TEAM IN SPORT & SPIRIT
At Varsity Brands, we believe every student deserves the opportunity to succeed and every educator wants to make a difference. It takes a team to make a real impact, and through our two divisions – BSN SPORTS and Varsity Spirit – and our network of 6,000+ employees and independent representatives, we are proud to partner with a wide range of educational institutions and club and professional sports to transform the student journey in SPORT and SPIRIT.
Location: Remote
WHAT YOU WILL DO:
The Director, Data Engineering will lead the team responsible for designing, building, operating, and continuously enhancing Varsity Brands’ enterprise data platform. This role will own the strategy and execution for our Snowflake-based data warehouse and future lakehouse capabilities, ensuring the platform delivers trusted, scalable, and secure data products that support analytics, business intelligence, operational reporting, and AI use cases.
Reporting to the SVP, Data and AI, this leader will oversee data engineering, database engineering, replication, transformation pipelines, data governance, and foundational data services. The Director, Data Engineering will partner closely with the leadership, enterprise architecture, application engineering, security, infrastructure, product, and business teams to modernize data capabilities and establish engineering practices that enable speed, reliability, governance, and measurable business value.
HOW YOU WILL DO IT:
Data Platform Leadership
Lead the enterprise data engineering team responsible for the Snowflake-based data warehouse and future lakehouse architecture
Define and execute the roadmap for scalable, secure, and high-performance data platform capabilities
Establish platform patterns that enable analytics, reporting, data science, machine learning, and generative AI use cases
Partner with the leadership to align platform investments with business priorities, enterprise architecture, and AI strategy
Drive modernization of data architecture, including data modeling, ingestion, storage, transformation, orchestration, metadata, observability, and governance
Data Engineering & Pipelines
Own the design, build, and operational support of data replication and transformation pipelines across enterprise systems
Ensure pipelines are reliable, testable, observable, and optimized for performance, cost, and data quality
Lead the implementation of engineering standards for ELT/ETL, orchestration, CI/CD, monitoring, incident response, and production support
Build reusable frameworks and patterns that improve delivery speed and reduce operational complexity
Ensure data products are accurate, well-documented, discoverable, and aligned to business definitions
Database Engineering
Lead database engineering for OLTP databases, Operational Data Stores, and Master Data Management platforms hosted in AWS
Oversee database design, performance tuning, reliability, scalability, backup/recovery, monitoring, and lifecycle management
Partner with application engineering teams to support transactional database needs and operational data patterns
Establish standards for database security, access management, schema changes, release practices, and operational excellence
Support enterprise MDM capabilities that improve consistency, quality, and trust in core business data
AI & Advanced Analytics Enablement
Ensure the data platform provides foundational data assets required to support AI, machine learning, and advanced analytics
Collaborate with data science, AI engineering, analytics, and business stakeholders to identify, prioritize, and deliver high-value data products
Enable governed access to curated, high-quality data for experimentation, model training, inference, reporting, and decision support
Support the evolution of data architecture to meet emerging AI and lakehouse requirements
Data Governance Program Leadership
Lead the implementation and ongoing oversight of the enterprise data governance program
Establish governance standards, operating models, stewardship practices, data ownership frameworks, and decision-making processes
Partner with business and technology leaders to define critical data domains, data owners, data stewards, and governance priorities
Oversee data quality, metadata management, lineage, cataloging, access controls, retention practices, and policy adherence
Ensure governance practices are embedded into data platform delivery, data pipeline development, database engineering, analytics enablement, and AI use-case support
Drive alignment between data governance, security, privacy, compliance, enterprise architecture, and business reporting needs
Promote a culture of trusted, well-documented, responsibly managed data across the organization
Leadership Responsibilities
The Director, Data Engineering will lead and develop a high-performing data engineering organization while establishing the operating model, talent, and engineering practices necessary to deliver secure, scalable, and reliable enterprise data platforms:
Lead, coach, and develop a team of data engineers and database engineers
Build a culture of technical excellence, accountability, collaboration, documentation, and continuous improvement
Define roles, delivery processes, performance expectations, and career development paths for the team
Manage vendor, platform, and implementation partners as needed
Translate technical complexity into clear business-facing roadmaps, tradeoffs, risks, and outcomes
Success Metrics
Within the first 12–18 months, success will include:
Deliver a scalable, secure, and highly available enterprise data platform supporting analytics, reporting, and AI initiatives
Improve data pipeline reliability, observability, and data quality across enterprise systems
Establish enterprise data governance standards, stewardship, and operating model adoption
Develop and retain a high-performing data engineering organization with clearly defined roles and career paths
Deliver prioritized platform modernization initiatives on schedule and aligned with business priorities
Improve platform performance, operational efficiency, and cloud cost optimization
Increase business adoption of trusted enterprise data products and self-service analytics
QUALIFICATIONS:
Knowledge, Skills, Abilities
The ideal candidate will demonstrate the following leadership capabilities:
Strategic platform thinking
Enterprise data architecture
Engineering excellence
Operational reliability
People leadership and talent development
Stakeholder partnership
Data governance mindset
Business outcome orientation
Change leadership
Clear executive communication
Education, Certification and Experience
Required
Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Management, or a related field; equivalent experience will be considered
10+ years of experience in data engineering, database engineering, data platform architecture, or related technology roles
Strong hands-on background with cloud data platforms
Strong hands-on experience with AWS-hosted database and data services
Strong understanding of OLTP database platforms, Operational Data Stores, and Master Data Management concepts
Experience building and supporting enterprise-grade data replication, ingestion, and transformation pipelines
Familiarity with modern data engineering practices including orchestration, CI/CD, automated testing, data quality, observability, and production support
Strong understanding of data modeling, SQL performance optimization, metadata management, access controls, and data governance
Proven ability to partner with business, analytics, AI, application engineering, security, and infrastructure teams
Strong communication skills with the ability to influence technical and non-technical stakeholders
Preferred
Experience with lakehouse architecture and open table formats
Experience supporting AI, machine learning, or advanced analytics platforms
Experience with data transformation tools such as dbt or similar frameworks
Experience with replication, CDC, or streaming technologies
Experience with data catalog, lineage, quality, and observability tools
Experience leading data platform modernization or cloud migration initiatives
Experience in retail, sports, education, events, manufacturing, distribution, or multi-brand enterprise environments
Physical Demands and/or Work Environment
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
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Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities required of the employee for this job.
OUR VALUES
Service - We lead with heart. We champion community.
Passion - We love what we do. It fuels our purpose.
Integrity - We do what we promise. We own our actions and decisions.
Respect - We earn it by giving it. Because everyone deserves it.
Innovation - We never stop striving to be better. For ourselves and our community.
Transparency - We are committed to openness and honesty in everything we do.
OUR BENEFITS
We are committed to putting you and your families first. For benefits eligible roles, we offer a variety of choices and costs as well as program enhancements that align with our responsibility to elevate the employee experience. Some of our offerings include:
Varsity Brands companies are equal opportunity employers. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, citizenship, gender, sexual orientation, gender identity, veteran’s status, age or disability.
