At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, were the house of iconic brands including NEUTROGENA, AVEENO, TYLENOL, LISTERINE, JOHNSONS and BAND-AID that you already know and love.

Science is our passion; care is our talent.

Who We Are :

Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated.

We are passionate about insights, innovation and committed to delivering the best products to our customers.

With expertise and empathy, being a Kenvuer means having the power to impact 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 futureand yours.

For more information, click here.

Role Reports To : SR MANAGER SL OMNI CHANNEL.

Location : Asia Pacific, India, Karnataka, Bangalore.

Work Location : Hybrid.

What You Will Do :

The Lead Analyst is responsible for delivering high-impact analytics, data, and reporting solutions that enable better decision-making and measurable business outcomes.

This role combines strong data analysis, data engineering, and business partnership capabilities, leading through expertise, influence, empathy, and collaboration.

The Lead Analyst owns work end to end - from understanding business needs through delivery, adoption, and value realization-while setting high standards for analytical rigor, scalability, and reliability across CVD solutions.

In addition to core analytics responsibilities, this role places emphasis on building, scaling, and stabilizing data platforms, pipelines, and automation capabilities that enable efficient, repeatable, and reliable analytics delivery across customers and teams.

Core Responsibilities & Expectations :

- Deliver end-to-end analytics solutions spanning data ingestion, transformation, modeling, reporting, and insight generation.

- Design, build, and support scalable data pipelines that ensure timely, reliable, and high-quality data availability.

- Apply strong data modeling practices to support consistent metrics, reusable datasets, and downstream analytics and reporting.

- Partner closely with business stakeholders to translate requirements into durable, scalable analytics solutions.

- Ensure analytics outputs are production-ready, well-documented, and aligned to defined business use cases.

- Identify opportunities to automate manual processes, reduce operational overhead, and improve speed to delivery.

- Lead through influence by setting technical standards, sharing informed opinions, and constructively challenging designs and approaches.

Areas of Emphasis :

- Build and maintain robust data ingestion, transformation, and validation workflows across multiple data sources.

- Enable analytics, reporting, forecasting, and self-service use cases through reliable and well-structured data foundations.

- Improve platform performance, scalability, and cost efficiency while maintaining data quality and governance standards.

- Support transitions and migrations (i.e. data platform or tooling changes) with minimal business disruption.

- Standardize patterns, processes, and reusable components to improve consistency and delivery velocity across teams.

Must Have :

- Strong hands-on experience with data analysis, transformation, and end-to-end analytics delivery.

- Experience designing and supporting scalable data pipelines in a modern cloud-based analytics environments (Databricks, Snowflake, Azure, SQL etc.

- Solid data modeling skills supporting consistent metrics, hierarchies, and reusable analytical structures.

- Proficiency in Python-based data engineering and analytics workflows.

- Experience delivering automation that reduces manual effort and improves reliability and timeliness.

- Strong collaboration and business partnership skills.

- Ownership mindset with accountability for platform reliability, efficiency gains, and downstream business enablement.

Good to Have :

- Experience with distributed data processing and transformation approaches (i.e., PySpark-class workloads).

- Exposure to analytics enablement for forecasting, planning, and performance management use cases.

- Experience supporting multi-team or contractor-based delivery models.

- Familiarity with data governance, access management, and data quality monitoring.

- Prior CPG, retail, or customer analytics platform experience.

Ways of Working & Leadership Expectations :

- Leads through expertise, influence, and collaboration rather than formal authority.

- Works closely with business and delivery partners to ensure data foundations enable real outcomes.

- Demonstrates strong self-awareness, accountability, and constructive challenge.

- Continuously improves platforms, processes, and patterns to increase effectiveness and scalability.

If you are an individual with a disability, please check our Disability Assistance page for information on how to request an accommodation.