Sr. Analyst, Data Engineering

Description

Kenvue is currently recruiting for:

Sr.

Analyst, Data Engineering

This position reports to the Manager, Data Engineering and is based at Bangalore, India.

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® Brand Adhesive Bandages that you already know and love.

Science is our passion; care is our talent.

Our global team is made up of ~ 22,000 diverse and brilliant people, 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 the 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.

For more information, click here .

Role reports to: Manager, Data Engineering

Location: Bangalore, India

Travel %: up to 10%

What you will do

As the Sr.

Analyst, Data Engineering, you will play a pivotal role in designing and prototyping cutting-edge solutions that empower our Operations with timely and relevant data.

You'll explore new tools and build cost-effective solutions using the powerful Azure Data Platform and Azure Databricks.

In this position, you will also lead and inspire our cross-vendor Data Engineering team, driving key initiatives that shape the future of our organization.

Key Responsibilities

• Develop, customize, and manage integration tools, databases, warehouses, and analytical systems

• Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products

• Adhere to 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

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

• Deploy data models 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.

• Monitor the overall performance and stability of the system; adjust and adapt automated pipeline as data, models, and/or requirements change

• Work with the Data Asset and Capability teams to identify the right data sources and finalize the data architectures for optimal data extraction and transformation

• 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 ...