Data Strategy and Governance Lead

About the job

Data Strategy and Governance Lead Description - Job Summary Define and lead the Finance Data Strategy and Governance agenda to establish a trusted, scalable and flexible enterprise data foundation for Finance based on its business priorities and transformation goals. The role will ensure that Finance data is trusted, governed, accessible, secure and AI-ready , enabling large scale Finance transformation. The data should be ready for automation, advanced analytics, AI at scale. The leader will establish the governance operating model for data ownership, stewardship, quality, standards, access, privacy and security, while being aligned with company’s data policy and frameworks. The lead should support data democratization for Finance users. Responsibilities

- Define and maintain the Finance Data Strategy and roadmap , ensuring alignment with Finance priorities and transformation goals and evolving business needs.

- The Finance Data Strategy and roadmap need to be aligned with Finance Transformation roadmap .

- Design a scalable and flexible Finance data architecture that can support current and future requirements across analytics, automation, AI and digital transformation.

- Establish and lead the Finance data governance operating model , including: - data ownership and stewardship;

- decision rights and accountability;

- authority to create, modify and approve critical data;

- governance forums and escalation mechanisms;

- data policies, standards and controls.

- Define and monitor data quality standards and metrics , including dashboards and controls that provide visibility into data quality, exceptions and remediation progress.

- Govern critical Finance data domains and critical data elements , with clear ownership, business definitions and quality expectations.

- Drive data democratization by enabling Finance professionals and leaders to easily discover, access and use trusted data required for their roles.

- Define differentiated data access and control models based on business need, data sensitivity, regulatory requirements, security risk and company’s security management framework and in partnership with IT, Cybersecurity, Legal, Privacy and Enterprise Data teams.

- Define enterprise Finance data models, standardized KPI definitions and calculations to create consistent and trusted decision-making across Finance.

- Establish frameworks for metadata and lineage , ensuring Finance users understand where data comes from, how it is transformed and how it should be used. Align with company’s established data lineage tools.

- Partner with Finance, IT, and other functions to resolve cross-functional data issues and align enterprise data priorities.

- Data architecture should enable AI, GenAI, automation, and analytics scalable products .

- Support Finance data-literacy programs , enabling users to: - understand key Finance data and metrics;

- interpret data correctly;

- use governed data products;

- understand appropriate use of analytics and AI;

- make better data-driven decisions.

Education & Experience

- Preferably 10+ years of experience across data strategy, governance, architecture, data quality and enterprise transformation.

- Graduate or four-year degree in Economics, Finance, Mathematics, Statistics, Computer Science, Data Science or a related discipline, or equivalent professional experience.

- Demonstrated experience operating across business, Finance and Technology organizations and influencing senior stakeholders. Knowledge & Skills Data Strategy & Governance

- Finance Data Strategy

- Data Governance Operating Model

- Data Ownership & Stewardship

- Decision Rights & Accountability

- Data Quality Management

- Data Privacy & Security

- Data Access Governance

- Data Policies & Standards

- Metadata & Data Lineage

- Data Cataloging

- Enterprise Data Models

- Critical Data Elements

- Business Definitions & KPI Standardization

- Data Maturity Assessment Data Enablement

- Data Democratization

- Data Literacy

- Self-Service Analytics

- Data Products

- AI-Ready Data

- Data Integration

- Cloud Data Platforms

- Databricks

- Power BI

- SQL / Python Leadership

- Strategic Thinking

- Cross-Functional Influence

- Executive Communication

- Change Leadership

- Results Orientation

- Learning Agility

- Customer Centricity

- Digital Fluency AI & Analytics

- Artificial Intelligence / Generative AI

- Machine Learning

- Advanced Analytics

- Predictive Analytics

- Data Science

- Data Visualization

- Automation

#Li-Post

Job - Data & Information Technology Schedule - Full time Shift - No shift premium (India) Travel -

Relocation - Equal Opportunity Employer (EEO) -

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP’s   EEO Policy or read about your rights as an applicant under the law here: “ Know Your Rights: Workplace Discrimination is Illegal "