Senior Manager, Data Engineering

NCSA College Recruiting is the world's largest college recruiting platform, providing student-athletes with tools and access to college coaches. The Senior Manager, Data Engineering will lead a team responsible for the design and ongoing evolution of the enterprise data platform, ensuring it meets the analytical and operational needs of the company.

Responsibilities:

• 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
• 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
• 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
• 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
• 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

Requirements:

• 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