DELIVERY LEAD - DATA AND AI (REMOTE)

Job Summary:

Compass Data & AI (CDAI) is seeking a Delivery Lead – Data & AI to help drive the strategy, planning, and delivery of enterprise data, analytics, AI, and reporting initiatives across Compass Group.
This role serves as the primary liaison between business stakeholders and technical delivery teams, partnering with Analytics Engineering, Data Engineering, Architecture, Product Management, and business leaders to translate business priorities into scalable data and AI solutions.
The ideal candidate combines strong business acumen with technical curiosity and excels at bringing together cross-functional teams to deliver meaningful business outcomes. They are highly organized, proactive, and comfortable coordinating work across multiple technical teams while partnering closely with business stakeholders to ensure priorities remain aligned and delivery stays on track.

Responsibilities:

• Lead the intake, planning, and coordination of enterprise Data & AI initiatives from concept through delivery.
• Partner with business stakeholders to understand priorities, define business outcomes, and translate opportunities into actionable work for technical teams.
• Serve as the primary connection between business stakeholders and technical teams, ensuring the right work is understood, coordinated, prioritized, and successfully delivered.
• Collaborate with Analytics Engineers, Data Engineers, Architects, Product Managers, and business leaders to deliver scalable data products, analytics solutions, AI capabilities, and enterprise reporting.
• Work with engineering teams to define requirements, acceptance criteria, implementation approaches, and delivery priorities while ensuring solutions align with business objectives.
• Coordinate delivery activities across multiple initiatives by facilitating regular team planning and progress sessions, identifying dependencies, removing blockers, and keeping work moving forward using tools such as Azure DevOps and Jira.
• Partner with Data Governance, Security, Architecture, and Legal teams to support data access requests, data sharing, metadata management, governance, and compliance processes.
• Communicate priorities, project status, risks, dependencies, and recommendations to technical teams, business stakeholders, and leadership.
• Help improve delivery processes, stakeholder engagement, portfolio planning, and governance practices across the Data & AI organization.

Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Economics, Business, Analytics, or a related field, or equivalent experience.
• 4–6+ years of experience in Product Management, Product Ownership, Delivery Management, Business Analysis, Program Coordination, Analytics Delivery, or a similar role supporting technology and data initiatives.
• Experience partnering with both business and technical teams to deliver analytics, reporting, AI, or cloud data platform solutions.
• Strong ability to translate business objectives into clear requirements, implementation plans, and actionable work for technical teams.
• Excellent stakeholder management, communication, facilitation, and organizational skills.
• Strong analytical mindset with the ability to solve complex business problems using data.
• Proven ability to coordinate multiple initiatives simultaneously while balancing competing priorities.
• Comfortable working in fast-paced environments with evolving priorities and ambiguity.
   
  Preferred Qualifications
• Experience with modern data platforms such as Snowflake, dbt, SQL, Power BI, or similar technologies.
• Experience supporting enterprise reporting, analytics, AI, or self-service data initiatives.
• Familiarity with data governance, metadata management, data catalog platforms (e.g., Secoda), or enterprise data management practices.
• Experience using Azure DevOps, Jira, or similar work management platforms to coordinate delivery and track execution.
• Experience supporting enterprise functions such as procurement, supply chain, finance, operations, or other data-driven business organizations.