Data and AI Program / Delivery Manager

Data and AI Program / Delivery Manager

With over 20 years of experience, our global network of passionate technologists and pioneering craftsmen deliver cutting-edge technology and game-changing consulting to companies on the brink of transformation. Since 2001, we have grown from a Java company into a full-service digital consulting company with 4500+ professionals working on a worldwide ambition.

We are organized in complementary chapters – teams with a tremendous amount of knowledge and experience within a particular field, such as Agile, DevOps, Data and AI, Cloud, Software Technology, Functional Programming, Low Code, and Microsoft.

We help the world’s top 250 companies and category leaders overcome digital challenges, embrace innovation, adopt new technology, and implement new business models. In addition to high-quality consulting, we also provide offshoring and nearshoring services.

For more details, please visit www.xebia.com

Job Title : Data and AI Program / Delivery Manager

Location : Atlanta, GA (Hybrid 3days onsite 2 days remote)

Job Description : -

Job Summary :

We are seeking a Delivery Manager with a strong data background to lead the successful execution of data-centric projects and programs. This role bridges the gap between technical teams, SMEs and business / executive stakeholders, ensuring timely, high-quality delivery of data platforms, pipelines, analytics, and AI / ML initiatives. The ideal candidate combines deep project management skills with decent experience in data technologies and architecture.

Key Responsibilities :

• Lead end-to-end delivery of data projects including data lakes, data warehouses, ETL pipelines, and MLOps platforms.
• Define project scope, goals, and deliverables that support business goals in collaboration with stakeholders.
• Manage project timelines, budgets, risks, and resources across multiple concurrent initiatives.
• Ensure adherence to Agile, Scrum, or hybrid delivery methodologies.
• Act as the primary liaison between data engineering teams, business analysts, technical SMEs and executive stakeholders.
• Facilitate communication across cross-functional teams to ensure alignment and transparency.
• Drive sprint planning, backlog grooming, and retrospectives for data teams.
• Track and report KPIs such as delivery velocity, data quality metrics, and stakeholder satisfaction.
• Identify delivery bottlenecks and implement process improvements.
• Promote a culture of continuous learning and innovation within the team.