The VP, Finance Data Product Owner – P&L Data (India) is the execution lead for the P&L data product agenda on One Data Foundation, supporting the VP, Global Data Product Owner – P&L. The role starts with Revenue and Expense Accrual data and sits where Finance, Accounting and Technology meet. It works day to day with data producers, consumers and P&L process owners’ teams, and turns the Global Product Owner’s priorities into certified, reusable data products.
The leader works with process owners to understand how the data is used and what outcome it supports and documents the manual processes and adjustments on both the production and consumption sides. The goal is to raise productivity and efficiency and keep the data products golden by reducing manual manipulation and point-to-point sourcing. The role builds governance by design (CDEs, definitions, ownership, lineage, DQ rules and controls) into each product and uses AI and automation to modernize a largely waterfall and manual delivery lifecycle.
The Global Data Product Owner sets product strategy, priorities, the portfolio roadmap and senior stakeholder agreements. This role executes, recommends and escalates. Controllers, Global Accounting and FP&A own the process and the reported numbers, and Technology owns engineering and production operations.
KEY ACCOUNTABILITIES
1. Bridge Producers and Consumers
- Be the working-level link between upstream accrual data producers and downstream consumers, so issues are raised once, routed to the right producer and tracked to closure.
- Partner with P&L process owners’ teams (Controllers, Global Accounting, FP&A and other consumers) to understand how they use the data and the outcome they need. Surface pain points and new needs early to the Global Product Owner.
- Draft and maintain producer–consumer terms: definitions, scope, frequency, granularity, quality thresholds, ownership and issue handling, for approval by the Global Product Owner.
- Support the consumer forum by preparing the agenda and facts, and make differences in how consumers interpret or override the same data visible.
2. Understand and Reduce Manual Work
- Document the manual processes, adjustments and overrides on the production and consumption sides of each in-scope P&L process. Quantify the effort and find the root causes.
- Recommend and drive fixes: move adjustments upstream or into the product so they are made once and governed, remove spreadsheet dependencies, and stop point-to-point sourcing. Priorities are agreed with the Global Product Owner.
- Use AI and automation to speed requirements, metadata, CDE identification, lineage, DQ rules, documentation and testing, within agreed controls.
3. Execute the P&L Data Products
- Run day-to-day delivery of the accrual data products. Maintain the backlog, define requirements, and work with architecture and engineering on sources, transformations, business rules and lineage.
- Prepare each product for certification: definitions, CDEs, lineage, DQ rules and controls complete, reconciled to the authoritative source, and confirmed to meet accounting requirements.
- Fix issues at the source with producers, strengthen reconciliation, and maintain a shared business glossary.
- Publish and reuse on One Data Foundation, enhancing existing products before creating new ones, and support retiring legacy sources and BI reports in favor of certified data.
4. Report, Escalate and Lead
- Give the Global Product Owner clear, regular updates on progress, risks and decisions needed. Escalate early and prepare materials for senior stakeholder discussions.
- Work across time zones with agreed overlap hours, documented handoffs and clear written follow-up.
- Guide and develop team members in India as the work grows.
REQUIRED QUALIFICATIONS
- Significant banking or financial services experience in Finance, Accounting or P&L functions.
- Strong working knowledge of revenue and/or expense accruals, accounting concepts, controls and reconciliations.
- Solid grasp of data lineage, quality and governance principles, with the ability to analyze and validate data independently (for example, SQL) and reconcile it to source.
- Strong analytical and problem-solving skills, including the ability to analyze manual processes and adjustments to find root causes and efficiency opportunities.
- Experience working between business and technology teams, with the ability to influence without direct authority and work effectively with global stakeholders across time zones.
- Clear written and verbal communication that explains data issues in terms of business impact.
- Demonstrated curiosity and a record of improving ways of working through automation or AI.
Preferred
- Hands-on experience with Databricks, Power BI or similar platforms; working knowledge of SQL and data modeling.
- Exposure to billing, revenue or general ledger systems and how they integrate with reporting platforms.
- Experience with platform migration or re-engineering programs, and with leading complex, multi-team work.
- Familiarity with GenAI or machine learning use cases in Finance, and agile or product ownership experience.
- Background in regulated or audit-sensitive environments, including regulatory and external reporting.
- Professional qualification (CA, CPA, CFA) or a degree in Finance, Accounting, Data or a related field.
MEASURES OF SUCCESS
- Delivery: accrual data products prepared and certified against the agreed plan, with documented producer–consumer terms.
- Manual work: manual processes and adjustments documented for each in-scope P&L process, with a measurable reduction in manual manipulation, spreadsheet dependencies and point-to-point feeds.
- Consistency and reuse: one agreed definition per P&L measure, more consumers on the certified products, and fewer report-level overrides.
- Issue efficiency: fewer duplicate issues sent to producers and faster resolution.
- Reliability: timely updates, early escalation and clean handoffs, as rated by the Global Product Owner.
- Partnership: process owners and producers report the role is fair, responsive and effective.
LEADERSHIP PROFILE AND CANDIDATE CALIBRATION
1. Bridge-builder mindset (most important)
What good looks like
Sits between producers and consumers by choice. Explains each side’s constraints to the other, gets both to commit to a shared agreement, and follows up until it holds.
Watch-outs in candidates
Acts as a requirements taker or a ticket router. Describes the role as “gathering requirements” or “sending tickets.”
2. Curious about the manual work
What good looks like
Wants to see how consumers really use the data and finds the adjustments and spreadsheets behind it. Asks why until the root cause is clear.
Watch-outs in candidates
Accepts manual adjustments as normal. Reports what people do without asking why.
3. Ownership of execution
What good looks like
Acts as an owner, not an order-taker. Follows through, flags problems early and keeps the Global Product Owner informed without being asked.
Watch-outs in candidates
Waits for detailed direction or makes portfolio-level commitments without agreement from the Global Product Owner.
4. Reuse-first and governance by design
What good looks like
Defaults to one certified source and one definition. Builds CDEs, lineage, DQ rules and controls in as the product is built. Challenges point-to-point feeds and local copies.
Watch-outs in candidates
Builds a new dataset for each request. Treats governance as a separate sign-off step.
5. Curious and AI-forward
What good looks like
Questions waterfall and manual ways of working. Experiments with AI and automation and keeps controls intact.
Watch-outs in candidates
Defends the current process. Views AI as hype or as a replacement for judgment.
6. Works well across time zones
What good looks like
Communicates proactively and in writing. Builds trust with global partners, uses facts and resolves conflict early.
Watch-outs in candidates
Communicates only when asked, or escalates as the first move.
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