Job Description

Kenvue Is Currently Recruiting For a

Lead Data Engineer

What We Do

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.

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 future–and yours. For more information, click here.

Role Reports To

Data Engineering Manager

Location:

Asia Pacific, India, Karnataka, Bangalore

Work Location:

Hybrid

What You Will Do

As a Lead Data Engineer , you will Lead a team responsible for the build, support, and optimization modern data solutions and analytical products across the Azure Data Platform. You’ll design and manage robust data pipelines (Azure Data Factory, Azure Databricks, Data Lake, Spark.SQL). You will collaborate closely with business stakeholders, data engineers, and data scientists to maintain reliable, secure, and scalable data products that drive decision-making—particularly within Supply Chain and CPG contexts.

Key Responsibilities

Data Engineering Development Lead

Design, develop, customize, and manage data integration tools, data lakes, warehouses, and analytical systems on Azure.
Build, scale, and harden data pipelines (internal & external sources) using Azure Data Factory, Azure Databricks (PySpark/Spark SQL), Azure Data Lake, Azure Synapse, and Azure SQL.
Build and Deploy data pipelines into production environments by enriching the model with data stored in a Data Lakes or coming directly from data sources, configuring data attributes, managing computing resources, setting up monitoring tools, etc.
Mentor and Build a Data Engineering Support team composed of Data Engineering Resources
Own automation, observability, and monitoring frameworks—capturing operational KPIs and data quality metrics; set up alerting and runbooks.
Monitor performance & stability, triage incidents, and adapt pipelines as data/models/requirements evolve.
Build POCs on tool stack like Neo4j Graph db, Databricks, Fabric etc and suggest changes for cost optimization.
Implement best practices for systems integration, security (RBAC, Key Vault, RLS/OLS), performance, cost optimization, and data governance.
Work with the Data Asset and Capability teams to identify the right data sources and understand and build and support the data architectures for optimal data extraction and transformation for key business processes.
Test the reliability and performance of data engineering pipelines and support testing team with data validation activities
Partner with various Azure Engineering subject matter experts including project Managers and business team to scope and build customer facing content, modules, tools and proof of concepts
Research and cultivate in state-of-the-art data engineering methodologies, drive product innovation, and act as an Azure subject matter expert for other engineers
Apply DevOps/DataOps/Agile methodologies; manage version control (Git/Bitbucket) and CI/CD pipelines (Azure DevOps/Jenkins) for data and BI assets.

Required Qualifications

Bachelor’s degree in Engineering, Computer Science, Data Analytics, IT, or related field.

6-8 years of relevant experience across Azure Data Engineering and Power BI.

Hands-on expertise with:
Azure Databricks (PySpark/Spark SQL), Azure Data Factory, Azure Data Lake, Azure Synapse, Azure SQL
Data modelling, Performance Tuning
SQL/T-SQL (complex queries, stored procedures)
Experience of leading a Data Engineering team
Good scripting, data modeling and programming skills
Understanding of cloud architecture principles and best practices
Experience in the design and build of end-to-end solutions that meet business requirements and adhere to scalability, reliability, and security standards
Familiarity with version control systems like Bitbucket, Jenkins and DevOps practices for CI/CD pipelines

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