Analyst, Data Engineering

Analyst, Data Engineering

Ce que nous faisons

Chez Kenvue, nous réalisons le pouvoir extraordinaire des soins quotidiens. S'appuyant sur plus d'un siècle d'héritage et enraciné dans la science, nous sommes la maison de marques emblématiques - dont NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON'S® et BAND-AID® que vous connaissez et aimez déjà. La science est notre passion ; Le soin est notre talent.

Qui nous sommes

Notre équipe mondiale est composée de ~ 22 000 personnes brillantes avec une culture d'entreprise où chaque voix compte et chaque contribution est appréciée. Nous sommes passionnés par les idées, l'innovation et l'engagement à fournir les meilleurs produits à nos clients. Avec de l'expertise et de l'empathie, être un Kenvuer signifie avoir le pouvoir d'avoir un impact sur des millions de personnes chaque jour. Nous donnons la priorité aux personnes, nous nous soucions farouchement, nous gagnons la confiance grâce à la science et nous résolvons les problèmes avec courage - et nous vous offrons de brillantes opportunités ! Joignez-vous à nous pour façonner notre avenir et le vôtre. Pour plus d'informations, cliquez sur ici.

Role relève à :

Data Engineering Manager

Lieu :

Asia Pacific, India, Karnataka, Bangalore

Lieu de travail :

Hybride

Ce que tu vas faire

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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