Analyst, Data Engineering

Analyst, Data Engineering

Cosa facciamo

A Kenvue, ci rendiamo conto dello straordinario potere della cura quotidiana. Costruiti su oltre un secolo di tradizione e radicati nella scienza, siamo la casa di marchi iconici, tra cui NEUTROGENA®, AVEENO,® TYLENOL,® LISTERINE,® JOHNSON'S® e BAND-AID® che già conosci e ami. La scienza è la nostra passione; la cura è il nostro talento.

Chi siamo

Il nostro team globale è composto da ~ 22.000 persone brillanti con una cultura del posto di lavoro in cui ogni voce conta e ogni contributo è apprezzato. Siamo appassionati di intuizioni, innovazione e impegno a fornire i migliori prodotti ai nostri clienti. Con competenza ed empatia, essere un Kenvuer significa avere il potere di avere un impatto su milioni di persone ogni giorno. Mettiamo le persone al primo posto, ci prendiamo cura di noi, ci guadagniamo la fiducia della scienza e risolviamo con coraggio - e abbiamo brillanti opportunità che ti aspettano! Unisciti a noi per plasmare il nostro futuro e il tuo. Per ulteriori informazioni, fare clic su here.

Role riporta a:

Data Engineering Manager

Ubicazione:

Asia Pacific, India, Karnataka, Bangalore

Luogo di lavoro:

Ibrido

Cosa farai

Job Description

We are excited to announce an opening for Analyst at Kenvue.

Please find below the details of the role and its responsibilities.

Skills Required:

Data Engineering, Azure Databricks, Python ADF or Azure Data Factory, SQL,

Experience Range:

2 - 4 years

Job Description:

Role: Analyst - Data Engineering

Analyst, Data Engineering

This position reports to the Manager, Digital Solutions and is based at Bangalore, India.

Who we are

At , 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, .

Role reports to: Manager, Digital Solutions

What you will do

As the Analyst Data Engineering  you will play a pivotal role in supporting and

enhancing 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 support our Data Engineering

team, driving and supporting key initiatives and business processes that shape the future

of our organization.

Key Responsibilities

What We Are Looking For

Required Qualifications

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

analytical systems

• Manage and scale ETL 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 engineering dev team, other support teams,

Data science team) 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

• 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.

• 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

understand and build and support the data architectures for optimal data extraction

and transformation for key business processes.

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