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Data Analytics Operations Lead Engineer

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Kenvue recrute actuellement pour un :

Data Analytics Operations Lead Engineer

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 :

Sr. Director, Enterprise Data Products

Lieu :

Asia Pacific, India, Karnataka, Bangalore

Lieu de travail :

Entièrement sur place

Ce que tu vas faire

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 Products & Operations

Location: Bangalore, India

Travel %: up to 10%

 

What you will do 

Data & Analytics Operations Engineer (often called a DataOps Engineer) is a specialized role focused on the "production line" of data. They bridge the gap between data engineering (which builds the systems) and data analysis (which uses the data), ensuring that pipelines are automated, reliable, and secure. 

Core Responsibilities

  • Pipeline Engineering & Orchestration: Designing and/or maintaining scalable ETL/ELT pipelines using Azure Data Factory (ADF) or Databricks Workflows for ingestion and Azure Databricks (PySpark/SQL) for complex transformations.

  • Lakehouse Management: Implementing and optimizing Medallion Architecture (Bronze, Silver, Gold layers) using Delta Lake to ensure data consistency through ACID transactions.

  • DataOps & Automation: Automating deployments in a scrum of scrum environment, testing, and monitoring of data workflows using Azure DevOpsGitHub Actions, or CI/CD pipelines for Databricks notebooks and jobs.

  • User Feedback: Manage tickets intake and drive appropriate resolution by collaborating with other DevOps or Data Engineers.   

  • Governance & Security: Managing centralized access control, data lineage, and auditing across workspaces using Unity Catalog.

  • Performance & FinOps: Tuning Spark jobs (partitioning, Z-ordering, caching) for performance and monitoring cluster usage to optimize Azure and Databricks costs.

  • Operational Support: Providing L2/L3 support for production job failures, performing root cause analysis (RCA), and ensuring strict adherence to Service Level Agreements (SLAs)

  • Collaboration: Work closely with business analysts, data scientists, and DevOps engineers to ensure successful data platform implementations. 

  • Communication: Excellent communication and articulation skills especially when engaging with stakeholders.

Required Technical Skills

  • Cloud Platform: Mastery of Azure services, specifically ADLS Gen2Azure Data FactoryAzure Synapse, and Azure Key Vault.

  • Databricks Ecosystem: Expert knowledge of PySparkSpark SQLDelta Live Tables (DLT), and Databricks Workflows.

  • Programming: High proficiency in Python and SQL; experience with Scala or PowerShell is often a plus.

  • Infrastructure as Code (IaC): Experience in provisioning and managing Azure data resources.

  • Monitoring: Familiarity with Azure MonitorLog Analytics, and Application Insights for proactive alerting. 

Qualifications

  • Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related quantitative field.

  • Experience: 4 – 8 years in data engineering or DataOps, with at least 2 years specifically focused on the Databricks/Azure stack.

Preferred Certifications:

  • Microsoft Certified: Azure Data Engineer Associate

  • Databricks Certified Professional Data Engineer 

 

What’s in it for you

·    Competitive Total Rewards Package*

·    Paid Company Holidays, Paid Vacation, Volunteer Time & More!

  • Learning & Development Opportunities

  • Employee Resource Groups 

  • This list could vary based on location/region

 

*Note: Total Rewards at Kenvue include salary, bonus (if applicable) and benefits. Your Talent Access Partner will be able to share more about our total rewards offerings and the specific salary range for the relevant location(s) during the recruitment & hiring process.

 

Kenvue is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, protected veteran status, or any other legally protected characteristic, and will not be discriminated against on the basis of disability.

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