Lead, Data Engineering

Description

Kenvue is currently recruiting for:

Lead, Data Engineering

This position reports into Manager, Data Engineering and is based at Bangalore.

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® that you already know and love.

Science is our passion; care is our talent.

Our global team is made up with 22,000 diverse and brilliant people, passionate about insights, innovation and committed to deliver the best products to our customers.

With expertise and empathy, being a Kenvuer means to have the power to impact 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 .

What You Will Do

As the Lead, 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

• Build and own the automation and monitoring frameworks that capture metrics and operational KPIs for data pipeline quality and performance

• Implement 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

• 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 t...