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 future - and yours.

Role Reports To : Manager.

Location : Asia Pacific, India, Karnataka, Bangalore.

Work Location : Hybrid.

Position Summary :

What you will do :

- Good understanding of migration and modernization strategies and approaches.

- Helping business migrate and/or build Data, Analytics & AI workloads throughout their Azure journey towards production and expanding the azure infrastructure usage.

- Good understanding of Data factory, Databricks, Azure SQL.

- Staying current on latest Azure/Cloud innovations in order to conduct experiments, drive product improvement, and act as an Azure subject matter trainer for other engineers.

- Development, customize and manage integration tools, databases, warehouses and analytical systems with the use of data related instruments/instances.

- Create and run complex queries and automation scripts for operational data processing.

- Test the reliability and performance of each part of a system and cooperate with the testing team.

- Deploying data models into production environments.

- This entails providing the model with data stored in a warehouse or coming directly from sources, configuring data attributes, managing computing resources, setting up monitoring tools, etc.

- Support for setting up tools to view data, generate reports, and create visuals.

- Support to Monitoring the overall performance and stability of the system.

- Adjust and adapt the automated pipeline as data/models/requirements change.

- As per organizational & project priority responsibilities can be added later.

Tasks/Duties/Responsibilities :

- Support data pipelines from internal and external data sources to support new product launches and drive data quality across data products.

- Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality and performance.

- Support for implementing best practices around systems integration, security, performance and data management.

- Collaborate with internal clients (data science and product teams) to drive solutioning and POC discussions.

- Partner with the business, IT, and technical subject matter experts to ensure execution of enterprise-wide data engineering products & platform development.

- Implement DevOps, DataOps and Agile methodologies to improve KPIs like cycle times, consistency, and quality.

- Develop and optimize procedures to Productionalize data science models.

Other Duties :

- Participating in other organization wide activities as part of the duty.

Required Qualification :

Consider and identify qualifications potential applicants must possess in order to be considered for the position.

Basic Qualifications must be clearly stated, objective and relevant to this particular position.

Required Knowledge, Skills and Abilities :

- Excellent understanding of ETL cycle.

- Experience in the design and bu of services using Azure architecture is added advantage.

- Azure data engineering certification is good.

- Experience in using of Python/ PySpark and/or Scala for data engineering.

- Understanding of data types/ handling of different data models.

- Desirable to have experience with Spark, Kafka, Flask, Python, Neo4J Graph database.

- Experience with the Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Synapse, Databricks, deployment of Web Application (Azure) is must.

- Good scripting and programming skills.

Preferred Qualifications :

Preferred Minimum Education : Bachelor of Engineering.

Other : Azure Data Engineering Certification.

Preferred Area of Study: Data Engineering, Databricks,.

Preferred Related Industry Experience (if applicable) : Manufacturing & Logistics, IT Service.

Preferred Knowledge, Skills And Abilities :

- Azure Architect.

- Databricks.

- Azure Data Engineering.

- SQL.

- PLSQL.