Product Data Manager

Dyson; Bengaluru; On-site; INR 1,600,000 - 2,100,000; Full time

Job summary

Dyson is seeking a Data Product Manager to define and oversee the strategy and roadmap for data-driven assets and AI-enabled solutions. You will collaborate with business and technical teams to prioritize needs, translate requirements into concrete features, and drive delivery with agile practices.

In Bengaluru, you will partner with stakeholders to maximize business impact, monitor performance, and ensure compliance with privacy and governance standards.

Qualifications

• Experience gathering and translating business requirements into product features.
• Knowledge of data platforms, data modelling and analytics/reporting tools.
• Familiarity with AI architecture and evaluation methods.

Responsibilities

• Develop a deep understanding of business goals to inform delivery priorities.
• Collaborate with stakeholders to shape requirements and prioritize needs.
• Define and execute roadmaps driving measurable business outcomes.
• Work with technical teams to ensure timely delivery of data products.
• Communicate progress and results to stakeholders focusing on how data/AI meet goals.
• Advocate for best practices in AI/ML, data governance and UX.
• Monitor performance and reliability of data products with Data Operations.
• Define post-launch metrics and drive adoption and iteration.
• Drive change management and training as AI workflows are integrated.

Skills

Stakeholder management

Data platforms

AI/ML awareness

Product strategy

Tools

Jira

Confluence

Job description

Data Product Managers determine and oversee delivery of the strategy and roadmap for data-driven assets, products and solutions to achieve business outcomes and financial objectives. Their responsibilities include collaborating with technical and functional stakeholders to set priorities, managing delivery and operations, and providing direction and oversight to delivery teams. This role demands strong analytical mindset, bias for action and passion for building impactful data products in a dynamic environment.

Key Responsibilities

• Develop a deep understanding of business goals and processes to inform delivery priorities and recommendations for improvements.
• Develop strong relationships and regularly communicate with business stakeholders to shape requirements and prioritize needs. Translating business requirements into actionable product and technical features.
• Define and execute product roadmaps that drive measurable business outcomes, including planning resource allocation and team skill requirements.
• Work closely with technical teams to ensure timely delivery of high-quality data products and solutions, resolving obstacles and trade-offs as required.
• Communicate delivery progress and results to stakeholders, focusing on how data and AI solutions meet their business goals.
• Advocate for best practices in AI/ML, data management, data governance, and user experience into data products and solutions.
• Monitor performance and reliability of data products, coordinating with Data Operations to resolve outages, bugs, and performance issues.
• Define and monitor post-launch metrics, performance and user adoption, iterating on solutions to maximize sustained business impact.
• Drive change management, including training and supporting end users as AI workflows and analytics are integrated into their daily operations.
• Ensure alignment and adherence to corporate, financial and IT standards (e.g., architecture, privacy, compliance, security).
• Continuously track and evaluate emerging data/AI technology, industry trends, and best practices to drive innovation and inform product execution.
• Proficient with Agile methodologies and tools (e.g., Jira, Confluence). Experience writing clear product requirements, user stories, and acceptance criteria with the help of AI.
• Skilled in prioritizing features and managing backlogs based on business value and technical dependencies. Demonstrated effective collaboration with cross-functional teams (engineering, analytics, business, etc.).
• Strong understanding of data platforms, data modelling and analytics/reporting tools.
• Good understanding of AI architecture, evaluation testing and context engineering.
• Demonstrated ability to synthesize complex technical specifications into clear, actionable insights for non-technical stakeholders across both written and verbal communication.
• Demonstrated strong business acumen and partnership with senior stakeholders. Building buy-in, influencing stakeholders and keeping diverse teams aligned.
• Excellent problem-solving, critical-thinking, and organizational skills. Ability to thrive in ambiguous, fast-paced environments.
• Ownership mindset with a bias for action and accountability for delivering measurable results.