Scrum Master

The Scrum Master will play a key role in driving agile delivery across multiple workstreams within enterprise-scale Data & AI initiatives, operating under a Scrum of Scrums framework.

This role involves facilitating cross-functional teams working on data engineering, analytics, and AI/ML use cases, managing dependencies, ensuring delivery excellence, and promoting collaboration between business stakeholders, data platform teams, and AI/technology partners. The Scrum Master will uphold agile best practices, enable continuous improvement, and ensure alignment between business objectives and data-driven outcomes.

Candidates with consulting or enterprise transformation experience are highly preferred, as the role demands structured stakeholder management, strong understanding of data/AI lifecycles, and agile coaching across diverse business and technology teams.

Key Responsibilities:

Agile Delivery & Facilitation

• Facilitate daily stand-ups, sprint planning, sprint reviews, and retrospectives for data and AI teams.
• Lead Scrum of Scrums sessions to ensure visibility, synchronization, and dependency management across data pipelines, models, and platform teams.
• Maintain sprint health and drive consistent delivery velocity across data ingestion, transformation, and model development cycles.
• Ensure adherence to Definition of Ready (DoR) and Definition of Done (DoD), including data quality, model validation, and deployment readiness.
• Track sprint progress, identify risks (e.g., data availability, model performance), and remove impediments to maintain momentum.

Stakeholder & Data Ecosystem Management

• Act as a liaison between business teams, data engineers, data scientists, platform teams, and external AI/technology partners.
• Facilitate transparent communication across stakeholders on data dependencies, model outputs, and delivery timelines.
• Drive alignment on priorities, use cases, and deliverables across the Data & AI ecosystem.

Coaching & Continuous Improvement

• Coach teams on agile principles with a focus on DataOps and MLOps practices.
• Promote adoption of modern engineering practices including CI/CD for data pipelines, automated testing, and model lifecycle management.
• Encourage a culture of experimentation, data-driven decision-making, and continuous improvement.

Planning, Reporting & Governance

• Support program increment (PI) planning, release planning, and roadmap alignment for Data & AI initiatives.
• Maintain visibility of dependencies across data sources, platforms, and AI models using agile and project management tools.
• Provide regular status updates, dashboards, and insights to leadership for informed decision-making.
• Ensure proper documentation of data flows, model artifacts, and sprint outputs for governance and audit readiness.

Requirements

Qualifications & Experience:

• Bachelor’s degree in Computer Science, Engineering, or related discipline.
• Minimum 8 years of experience in IT project/product development, including 4 years as a Scrum Master or Agile Project Manager in an agile delivery environment.
• 2+ years of experience coaching and training individuals or teams in agile practices.
• Demonstrated experience facilitating meetings at multiple organizational levels using advanced facilitation techniques.
• 4+ years of experience using Agile tools (Jira, Azure DevOps, etc.) and collaboration platforms (Microsoft Teams, SharePoint, Confluence).
• Expert knowledge of Microsoft Project with at least 3 years of practical experience.
• 3+ years of experience with CI/CD, automated testing, and design thinking methodologies.
• Advanced working knowledge of Microsoft Office applications, including Outlook, Word, and Excel.
• Certified Scrum Master (CSM, PSM I/II) required; SAFe certification preferred.
• Consulting experience in digital transformation, AI, or enterprise delivery programs is highly desirable.

Key Competencies:

• Strong communication, leadership, and facilitation skills.
• Proven ability to manage multiple agile teams in a scaled delivery environment.
• Excellent problem-solving and conflict-resolution abilities.
• Deep understanding of agile delivery metrics and performance optimization.
• Ability to work collaboratively with cross-functional AI, IT, and business teams.
• High adaptability, resilience, and focus on delivering business value through technology.