Lead- Data Solutions and Analytics

Kenvue Inc.; Bengaluru; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Kenvue Inc. is seeking a Lead – Data Solutions and Analytics to manage Azure-based data pipelines and analytical products.

The role collaborates with data engineers, scientists, and business stakeholders to ensure reliable, scalable data solutions that enable informed decision-making across Supply Chain and Consumer Packaged Goods contexts. You will mentor a Data Engineering team, oversee production support, and drive governance, security, and performance improvements across the Azure Data

Qualifications

• Bachelor’s degree in Engineering, Computer Science, Data Analytics, IT, or related field.
• Experience leading a Data Engineering team and data assets in cloud environments.
• Strong data modeling, SQL/T-SQL, and performance tuning skills.
• Familiarity with DevOps/CI/CD pipelines and Bitbucket/Jenkins is beneficial.

Responsibilities

• Design, build, and manage data pipelines on Azure for scalable data products.
• Mentor and lead a Data Engineering team to deliver analytics solutions.
• Collaborate with stakeholders to ensure data reliability, security, and governance.
• Establish observability, monitoring, and incident response for data platforms.
• Drive governance, CAPA, and major incident processes across data platforms.

Skills

Leadership

Stakeholder management

Problem solving

Presentation skills

Education

Bachelor's degree in Engineering/Computer Science/Data Analytics

Tools

Azure Data Factory

Azure Databricks

Azure Data Lake

Azure Synapse

Azure SQL

Job description

Kenvue is currently recruiting for a: Lead- Data Solutions and Analytics- Support

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, JOHNSONS and BAND-AID Brand 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.

Role reports to:

Digital Solutions Manager

Location:

Asia Pacific, India, Karnataka, Bangalore

Work Location:

Hybrid

What you will do

Role: Lead- Data Solutions and Analytics

Shifts: flexible for any shifts.

Summary:

Ensures the day-to-day operation of data processing, telecommunications, network systems, software and hardware configuration and support, and information technology implementation company wide. Manages within the framework of established policies and procedures with accountability for all systems and their enhancements. At this level the role has increased responsibility including, but not limited to, additional skills, multiple lines/products, diverse teams, etc.

Job Description:

Lead- Data Solutions and Analytics

This position reports to Manager, Digital Solutions and is based at Bengaluru, IN

What you will do:

As a Lead – Data Solution and Analytics, 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), SQL development and Data Analysis. 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.

Note: This role includes production support, monitoring, and potential rotational shift coverage (including night shifts if required).

Key Responsibilities:

• 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.
• 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.
• Create reusable SQL scripts for reporting, data validation, and ETL processes.
• Design, develop, and optimize complex SQL/T-SQL queries, stored procedures, and performance tuning for large-scale datasets.
• Perform data profiling, cleansing, and validation to ensure accuracy and reliability. [ Data Analytics]
• Develop data models and analytical frameworks to support reporting and decision-making.
• 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.
• Implement best practices for systems integration, security (RBAC, Key Vault, RLS/OLS), performance, cost optimization, and data governance.
• Governance and Compliance
  • Establish clear policies and procedures for support operations.
  • Ensure compliance with industry standards and regulations (e.g., ITIL, ISO).
  • Regularly review and update governance frameworks.
• CAPA (Corrective and Preventive Action)
  • Define processes for identifying, documenting, and investigating non-conformances.
  • Implement corrective actions to address identified issues.
  • Develop preventive measures to mitigate future risks.
  • Monitor effectiveness of CAPA implementation.
• Major Incident Process
  • Establish criteria for what constitutes a major incident.
  • Define roles and responsibilities during major incidents (e.g., incident commander, communication lead).
  • Create a communication plan for stakeholders during incidents.
  • Conduct post-incident reviews to capture lessons learned and improve processes.
• Root Cause Analysis (RCA)
  • Develop a standardized approach for conducting RCA.
  • Utilize tools and techniques (e.g., 5 Whys, Fishbone Diagram) to identify root causes.
  • Document findings and ensure accountability for corrective actions.
  • Communicate insights and preventive measures across teams.
• Failure Mode and Effects Analysis (FMEA)
  • Identify potential failure modes in digital products or processes.
  • Assess the impact and likelihood of each failure mode.
  • Prioritize risks based on severity and probability.
  • Develop action plans to mitigate high-priority risks.
• Performance Metrics and Reporting
  • Define key performance indicators (KPIs) for support operations (e.g., incident response time, resolution time).
  • Implement regular reporting mechanisms to track and analyze performance.
  • Use data-driven insights to inform decision-making and continuous improvement.
• Training and Development
  • Provide ongoing training for support staff on processes and tools.
  • Foster a culture of continuous learning and improvement.
  • Encourage cross-functional collaboration to enhance support capabilities.
• Stakeholder Engagement
  • Maintain open lines of communication with internal and external stakeholders.
  • Gather feedback from users and stakeholders to improve support operations.
  • Ensure alignment between support operations and business objectives.
• Technology and Tools
  • Leverage appropriate tools and technologies for incident management and reporting.
  • Invest in automation where feasible to enhance efficiency.
  • Ensure systems are integrated for seamless information flow.
  • 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.
• Must have Time Management, Problem-Solving & Critical Thinking skills.
• Must have presentation and stakeholder management skills
• Leadership & People Management is mandatory.
• 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:

• Major Incident Process framework for effectively leading support operations in the realm of digital products, ensuring that processes such as CAPA, major incident management, RCA, and FMEA are systematically implemented
• 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)

Desired Qualifications

• 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

Certifications:

Microsoft Certified: Azure Data Engineer Associate (DP-203)

Databricks Data Engineer Associate/Professional

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