Lead Data SME

Kenvue is currently recruiting for:

Lead Data SME, Data Products

This position reports into Principal Solutions Architect, Global Data Products and is based in GCC, Bengaluru.

Who We Are

At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON’S® and BAND-AID® that you already know and love. Science is our passion; care is our talent. Our global team is made by 22,000 diverse and brilliant people, passionate about insights, innovation and committed to deliver the best products to our customers. With expertise and empathy, being a Kenvuer means to have the power to impact life of millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours.

What You Will Do 

As a Lead Commercial Data Subject Matter Expert, you will be responsible for shaping and governing Kenvue’s Commercial data foundations that power Digital Analytics and Data Science products. You will act as the bridge between Commercial business stakeholders and Data Engineering teams, ensuring that data models, definitions, and pipelines are business-aligned, scalable, and analytics-ready.

This role combines deep Commercial domain expertise (Sales, Customer, Product, Finance) with strong data modeling and data product thinking, enabling high-quality insights, advanced analytics, and AI-driven use cases.

Responsibilities:

Commercial Data Domain Leadership

• Serve as the primary data SME for Kenvue Commercial domains, including Sales, Marketing, Customer, Product, Pricing, Promotions, and Revenue.
• Translate Commercial business processes and KPIs into clear, standardized data definitions, metrics, and hierarchies.
• Act as a trusted advisor to Commercial stakeholders on how data can be leveraged to drive business outcomes.

Data Modeling & Architecture Guidance

• Partner closely with Data Engineering teams to design, review, and validate conceptual, logical, and physical data models for Commercial domains.
• Ensure data models are optimized to support analytics, reporting, and advanced data science use cases (e.g., forecasting, optimization, digital analytics).
• Guide best practices for dimensional modeling, fact/dimension design, and domain-oriented data products.

Commercial Data Products Enablement

• Enable the development of Commercial data products that power dashboards, Digital Analytics, and Data Science/AI solutions.
• Ensure data products are fit-for-purpose, reusable, and scalable across regions, brands, and channels.
• Collaborate with Analytics and Data Science teams to ensure data structures support modeling, feature engineering, and experimentation.

Requirements Translation & Backlog Support

• Work with Commercial teams to understand analytical and reporting needs and translate them into clear data requirements for engineering teams.
• Support Product Owners and delivery teams with domain context, acceptance criteria, and validation of outputs.
• Review data outputs to ensure they accurately reflect business logic and Commercial realities.

Data Quality, Governance & Standards

• Define and uphold data quality rules, business validations, and reconciliation logic for Commercial data.
• Contribute to Data Governance initiatives, including Business Glossary, Metadata Management, and Data Catalog adoption.
• Ensure alignment with data privacy, security, and compliance standards across Commercial datasets.

Performance Measurement & Continuous Improvement

• Define and monitor data quality and usability metrics for Commercial data products.
• Continuously identify gaps, redundancies, and opportunities to improve Commercial data foundations.
• Stay abreast of emerging trends in CPG Commercial analytics and data product design.

What We Are Looking For

Required Qualifications

• Typically requires 8+ years of relevant experience with a Bachelor’s degree; or 6+ years with a Master’s degree; or a PhD with 5+ years in Technology, Data Engineering, Computer/Software Engineering, Statistics, or related fields.
• 3+ years of hands-on experience in CPG/Retail, with strong understanding of Commercial domains such as Sales, Customer, Product, Pricing, Promotions, Trade Spend, and Finance.
• Proven experience working as a Data SME, Data Domain Lead, Data Product Lead, or similar role supporting analytics and AI use cases.
• Strong understanding of data modeling concepts, including dimensional modeling, star/snowflake schemas, and analytical data design.
• Experience partnering with Data Engineering teams to guide data architecture and model design.
• Solid understanding of how data supports Digital Analytics and Data Science products.
• Strong analytical mindset with the ability to connect business questions to data structures.
• Excellent communication skills, with the ability to explain complex data concepts to non-technical Commercial stakeholders.
• Experience working with Data Governance frameworks, including Business Glossary, Metadata Management, and Data Catalogs.
• Understanding of data privacy, security, and compliance considerations in enterprise data environments.
• Experience working in Agile / product-oriented delivery models.

Desired Qualifications

• Conversant with SQL; working knowledge of Python is a plus.
• Experience working in Retail or CPG Commercial analytics environments.
• Familiarity with cloud-based data platforms and modern data stacks.
• Prior exposure to supporting advanced analytics, ML, or AI-driven Commercial use cases.

What’s In It For You

• Competitive Benefit Package
• Paid Company Holidays, Paid Vacation, Volunteer Time, Summer Fridays & More!
• Learning & Development Opportunities
• Employee Resource Groups 

Kenvue is proud to be an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.