Job highlights

- The TPM owns the Sales vertical product direction and business outcomes while partnering with platform Product Owners,Data Architects,Business Analysts,Scrum Masters,engineering,quality and compliance teams that retain accountability for their respective platform,architecture and delivery responsibilities. Key Responsibilities

Job Title Technical Product Manager, Lilly USA DAAI

Location

India - Bangalore

Note: Roles are posted at the lowest level of a band. Employees hired into banded positions transfer at their current level, despite the level indicated in the posting.

Path/Level

P3

Role Overview The Technical Product Manager (TPM) owns the product vision, roadmap, prioritization and value realization for Lilly USA Commercial Sales data and analytics products. The role translates the needs of Sales Operations, field leadership and commercial teams into trusted, reusable data products and analytical capabilities that improve field effectiveness, customer engagement and business decision-making.

This individual-contributor role combines strong Commercial Sales stakeholder partnership with formal product management accountability. It moves beyond demand intake and status coordination to owning product outcomes, roadmap decisions, prioritization, adoption and measurable business value.

The TPM owns the Sales vertical product direction and business outcomes while partnering with platform Product Owners, Data Architects, Business Analysts, Scrum Masters, engineering, quality and compliance teams that retain accountability for their respective platform, architecture and delivery responsibilities.

Key Responsibilities

- Product vision, strategy and roadmap
- Define and communicate a multi-quarter data-product vision and roadmap for Commercial Sales, aligned with Commercial Unit priorities and the broader Data AI strategy.
- Translate business problems such as field effectiveness, targeting and customer engagement into validated product opportunities, data requirements and measurable outcomes.
- Prioritize the roadmap and backlog using business value, urgency, strategic alignment, effort, risk, compliance, capacity and dependency trade-offs; make and defend scope decisions with leadership.
- Maintain a transparent roadmap, release outlook and product lifecycle plan, clearly communicating changes in priorities, capacity, funding or dependencies.
- Align the Sales roadmap with reusable enterprise capabilities, platform roadmaps and relevant AI innovation initiatives before approving vertical-specific development.

- Product discovery and data-product definition

- Lead structured discovery with field users, Sales Operations, reporting teams to understand decisions, workflows, unmet needs and pain points before defining solutions.




- Validate problems and proposed product concepts through interviews, workflow observation, prototypes, data analysis, usability testing and field feedback.
- Define the business contract for each Sales data product, including intended consumers, decision use cases, product grain, key identifiers, business definitions, source systems, refresh expectations, quality thresholds, access requirements and service expectations, in partnership with the Business Analyst and Data Architect.
- Maintain a clear product catalogue covering product purpose, business owner, product owner, consumers, lifecycle status, dependencies, service expectations and adoption measures.

- End-to-end product delivery and acceptance

- Own product outcomes from validated prospect through production adoption, including scope, prioritization, release decisions, enablement and post-launch value tracking.
- Own product priorities, backlog ordering and timely scope decisions; partner with the Business Analyst to translate outcomes into epics, features, user stories, data requirements and acceptance criteria.
- Partner with the Scrum Master so planning refinement, reviews and delivery ceremonies support product priorities and timely decisions.
- Work with data engineers, analysts, ML engineers, quality teams and architects to resolve product questions and make informed value, usability, risk and sequencing trade-offs.
- Establish business acceptance criteria, coordinate UAT with authorized Sales stakeholders and secure business sign-off before release.
- Ensure critical Sales measures are reconciled across source systems, data products and consuming reports before production adoption.
- Coordinate product acceptance and operational handover to downstream analytics and reporting teams, including documentation, access, support ownership and known limitations.
- Track delivery and product health, proactively surfacing risks, dependencies, quality concerns, cost considerations and mitigation decisions.

- Stakeholder, portfolio and operating-model leadership

- Act as the single point of accountability and voice of the product for Commercial business partners, Sales Operations, field leadership and technology stakeholders.
- Lead regular Sales product reviews covering roadmap, value realized, adoption, product health, dependencies, risks and decisions required.
- Lead quarterly demand,



capacity and sequencing discussions for the Sales data-product portfolio, balancing business value, urgency, strategic alignment, risk, technical dependencies and available delivery capacity.
- Assess existing enterprise data products, approved patterns and reusable platform capabilities before starting new development.
- Contribute to maintaining the Sales DAAI operating model, decision rights and RACI, recommending updates when product, platform or delivery accountabilities change.
- Provide concise executive updates and evidence-based investment recommendations, including the consequences of funding, capacity and sequencing decisions.

- Data, AI and regulated-environment stewardship

- Champion and apply architecture, data-governance, privacy, security, quality and compliance standards established by the accountable enterprise teams.
- Promote trusted business definitions, data quality, lineage, appropriate access and a consistent source of truth for Sales and Commercial measures.
- Identify and validate Sales problems that may benefit from analytics, machine learning, generative AI or agentic capabilities.
- Partner with Business Analysts and engineering teams to assess feasibility, data readiness, responsible-AI considerations and measurable business value.
- Support the transition of successful proofs of concept into governed, supportable and adoptable Sales products.

- Value realization, adoption and lifecycle management

- Define success measures before investment and track outcomes after release, using appropriate business, product, data-quality, adoption and delivery measures.
- Drive change management, training, communications and field enablement so intended users adopt and benefit from the products.
- Continuously improve products through evidence-based releases, address low adoption or quality concerns and retire low-value or duplicative capabilities.

- Role Accountability and Decision Rights

- The TPM is accountable for why the product is needed, whom it serves, what outcomes it must deliver, what is prioritized and whether value is realized. The TPM partners with the Business Analyst on detailed requirements, the Scrum Master on delivery ceremonies, the Data Architect on architecture and governance standards, engineering and quality teams on implementation and validation, and platform Product Owners on reusable capabilities and technical roadmaps.

Qualifications and Skills

Relevant experience in technology, data, analytics or Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Technical Product Manager - Data Analytics & AI (Bengaluru)
🏢 Eli Lilly
📍 Bengaluru