Job Description

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.