About NCSA College Recruiting

NCSA College Recruiting is the world largest college recruiting platform, providing student-athletes content, tools, coaching and access to a network of 40,000 college coaches across 37 sports. NCSA is an online experience of IMG Academy, the world’s leading sports education brand and one of the Best and Brightest Companies to Work For in the Nation in 2024 and Top Remote Places to Work in 2024. IMG Academy provides a holistic education model that empowers student-athletes to win their future, preparing them for college and for life. Additional on-campus and online experiences include:

• Boarding school and camps, via a state-of-the-art campus in Bradenton, Fla.
• Online coaching via IMG Academy+, with a focus on personal development through the lens of sport and performance

Position Summary:

We are seeking a Senior Manager, Data Engineering, to lead a team of data engineers responsible for the design, building, and ongoing evolution of our enterprise data platform. This role sits at the intersection of technology, architecture, and business outcomes. You will be accountable for translating analytical and operational needs into a scalable, reliable, and well-governed data platform that supports decision-making across the company.

This is a hands-on leadership role requiring strong technical depth, proven people management skills, and the ability to partner effectively with peers within the Data organization, and cross functionally with engineering, product, and cloud operations.

Position Responsibilities:

Technical & Platform Leadership

• Own the end-to-end delivery of the enterprise data warehouse, from architectural designs through production release and operational support.
• Establish and evolve data engineering standards for data modeling, ingestion, transformation, testing, and deployment.
• Ensure solutions are scalable, performant, secure, and aligned with enterprise architecture principles.
• Drive best practices around CI/CD, data quality, observability, monitoring, and reliability People Leadership.
• Lead, mentor, and grow a team of data engineers across varying experience levels.
• Set clear expectations, provide regular feedback, and support career development and performance management.
• Foster a culture of engineering excellence, accountability, and continuous improvement Delivery & Execution.
• Partners with product, business intelligence, data science, and operations teams to prioritize work and deliver high-value data solutions.
• Balance new development with technical debt reduction and platform stability.
• Own release planning and ensure predictable, high-quality delivery.

Stakeholder Partnership

• Act as a trusted technical advisor to business intelligence, data science, and operations leaders.
• Translate business requirements into well-designed data solutions.
• Communicate complex technical concepts clearly to non-technical audiences.

Governance & Operational Excellence

• Ensure data accuracy, lineage, and governance standards are met.
• Support regulatory, security, and compliance requirements.
• Monitor and optimize cost, performance, and operational health of the data platform.

What Success Looks Like

• The data and information in the data warehouse is trusted and widely adopted.
• Data delivery is predictable, high quality, and aligned to business priorities.
• Data engineers are engaged, growing, and delivering consistently.
• Business stakeholders view the data engineering team as a strategic partner.
• The data warehouse is performant and scalable.

Knowledge, Skills and Abilities:

• 10+ years of experience in data engineering, including 4+ years in a people-management role.
• Deep experience designing and building enterprise-scale data warehouses.
• Strong SQL and data modeling experience (dimensional, normalized, and hybrid models).
• Experience with modern data platforms (cloud data warehouses, ELT frameworks, orchestration tools, etc).
• Proven ability to lead complex, cross-functional data initiatives.
• Experience operating data platforms in a cloud environment (we are an AWS shop).
• Familiarity with analytics engineering and semantic layer concepts.
• Experience supporting self-service business intelligence and data science use cases.
• Strong understanding of data governance, quality frameworks, and metadata management.