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Ref #
W176747
State/Region
Karnataka
Department
Data Analytics
Location
India
City
Bangalore

COMPANY DESCRIPTION

Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.

At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

POSITION OVERVIEW

The Scrum Master (Manager – Data Products) enables reliable, high-quality delivery of Ralph Lauren’s enterprise Data Product portfolio, supporting teams that build and operate shared data assets, analytical datasets, and AI-ready data foundations.
Working closely with Data Product Managers, Data Engineering, Analytics, and Governance teams, this role ensures agile ways of working are applied effectively to data product delivery—improving flow, predictability, transparency, and continuous improvement. The Scrum Master focuses on execution discipline, dependency management, and team effectiveness, while product direction and prioritization remain with Product Managers.
At a manager level, this role brings experience navigating complex data programs, coordinating across multiple data domains, and coaching teams and stakeholders in pragmatic, outcome-oriented agile practices.

ESSENTIAL DUTIES & RESPONSIBILITIES

1. Agile Delivery for Data Products
• Facilitate agile ceremonies (sprint planning, stand-ups, reviews, retrospectives) for data product teams.
• Support consistent execution of data product backlogs aligned to agreed roadmaps and enterprise priorities.
• Help teams plan, sequence, and deliver data assets incrementally and predictably.
• Ensure visibility into delivery progress, risks, dependencies, and impediments.
2. Partnership with Data Product Managers
• Work closely with Data Product Managers to support backlog readiness, sprint goals, and delivery cadence.
• Help translate product roadmaps into executable sprint plans without owning prioritization decisions.
• Provide delivery insights such as capacity, throughput, and dependency risks to inform planning.
• Support product reviews and stakeholder updates with execution-focused perspectives.
3. Team Coaching & Continuous Improvement
• Coach data engineering, analytics, and platform teams on agile and lean delivery practices in a data context.
• Identify process, coordination, or dependency issues impacting delivery effectiveness.
• Facilitate retrospectives that drive practical improvements in flow, quality, and collaboration.
• Encourage accountability, transparency, and shared ownership within delivery teams.
4. Dependency & Stakeholder Management
• Coordinate across data engineering, analytics, governance, platform, and upstream/downstream teams.
• Help manage interdependencies across data domains, pipelines, and shared platforms.
• Proactively surface delivery risks, delays, or conflicts to Product Managers and leadership.
• Support alignment between delivery timelines and enterprise data priorities.
5. Metrics, Reporting & Delivery Insights
• Track delivery metrics such as sprint predictability, throughput, flow efficiency, and stability.
• Provide insights into delivery health, bottlenecks, and maturity trends.
• Ensure metrics are used to enable transparency and improvement—not enforcement.
• Contribute to leadership reporting with objective views of delivery performance.
6. Data Ways of Working & Maturity
• Support adoption of consistent agile delivery practices across data product teams.
• Adapt agile practices to suit data engineering and analytics realities (dependencies, quality checks, platform work).
• Collaborate with other Scrum Masters and delivery leads to strengthen enterprise data delivery maturity.
• Promote pragmatic agility over rigid frameworks.

EXPERIENCE, SKILLS & KNOWLEDGE

Required

• 7–10 years of experience as a Scrum Master, Agile Delivery Lead, or equivalent role.

• Strong experience supporting data engineering, analytics, AI, or enterprise data platform teams.

• Solid understanding of Agile, Scrum, and Lean delivery principles applied to data products.

• Proven ability to work effectively with Data Product Managers and technical teams.

• Strong stakeholder management and communication skills in complex environments.



Preferred

• Experience delivering enterprise data products, shared data assets, or analytical platforms.

• Background in retail, consumer goods, or other data-intensive industries.

• Experience coordinating delivery across multiple data domains or programs.

• Scrum / Agile certifications (CSM, PSM, SAFe, etc.).

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