Data Product Manager

Job Title: Data Product Manager

Location: Hyderabad, India

Mode: Hybrid

This role is a high-impact Data Product Manager position at the center of a large-scale transformation to build a modern, AI-ready data ecosystem. You will act as the critical bridge between business stakeholders, data engineers, and AI teams, translating business needs into scalable data and AI solutions that deliver real outcomes. With ownership of end-to-end data products, youll define product vision, drive execution through agile planning, and ensure strong alignment between technology and business priorities. The role also offers the opportunity to implement a Data-as-a-Product mindset, shaping foundational platforms like data lakes and warehouses while directly influencing key domains such as supply chain, commercial, and finance. Ultimately, its a strategic position where you connect enterprise data investments to measurable business value and play a key role in advancing the organizations AI ambitions.

Your key responsibilities:

• Define product vision strategy for Data and AI products aligned with organizational goals.
• Translate business needs into technical priorities, ensuring clear product capabilities.
• Own and manage the product backlogprioritization, sequencing, and clarity of deliverables.
• Lead sprint and quarterly planning for data and AI product teams.
• Collaborate with data engineers and architects to build scalable, robust data solutions.
• Drive delivery of foundational data platforms and ensure successful execution of key initiatives.

You bring:

• Strong technical foundation in data systems, pipelines, AI engineering, and streaming architectures.
• Ability to write clear product requirements, user stories, and acceptance criteria.
• Strong analytical and customer research skills to determine product needs.
• Capability to communicate complex technical concepts to non-technical stakeholders.
• High ownership and organizational skills with outcome-driven execution.
• Familiarity with cloud platforms (GCP, AWS, Azure) and modern data/AI ecosystems.