Data Product Ownership & Strategy :

- Define and own the vision, roadmap, and backlog for data products aligned to business priorities.

- Translate business requirements into scalable data products such as datasets, dashboards, APIs, and analytics solutions.

- Drive product lifecycle management from ideation, design, build, testing to deployment and continuous improvement.

- Ensure reusability and standardization using data product frameworks (medallion architecture, semantic layer).

- Prioritize backlog based on business impact, feasibility, and platform strategy.

- Build and maintain value realization dashboards for leadership.

- Continuously refine products based on usage insights and feedback.

Business Stakeholder Engagement :

- Act as the primary interface between business units and data teams.

- Collaborate with stakeholders to identify high-impact use cases.

- Convert ambiguous business problems into structured, data-driven solutions.

- Drive alignment through regular stakeholder reviews, demos, and feedback loops.

- Ensure high adoption by focusing on user experience and business outcomes.

End-to-End Project Ownership :

- Manage multiple concurrent data initiatives across business units.

- Define and track project scope, milestones, timelines, risks, and dependencies.

- Lead delivery using Agile / Scrum or hybrid models.

- Ensure coordination across data engineering, analytics, visualization, and business teams.

- Proactively manage risks, escalations, and issue resolution.

- Manage delivery through external vendors and partners.

- Ensure alignment to SOW, timelines, and SLAs.

- Monitor vendor performance and quality of deliverables.

- Drive accountability and resolve delivery bottlenecks.

Cross-Functional Team Leadership :

- Drive collaboration across Data Platform, Engineering, BI, Governance and vendors teams.

- Ensure teams are aligned on goals, priorities, and delivery timelines.

- Ensure all data products align with enterprise data platform strategy (Lakehouse, AWS/GCP).

- Collaborate with architecture teams to ensure Scalability and performance, Data quality, lineage, and governance compliance.

- Promote data reuse and asset standardization across use cases and drive adoption of best practices in data modeling and design.

Experience :

- 10- 15 years in Data / Analytics / Product / Program Management roles.

- Experience in managing large-scale data or analytics projects.

- Exposure to cross-functional and global teams.

- Experience in Manufacturing domain preferred.

- Carrier is An Equal Opportunity/Affirmative Action Employer.

- All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.