Job Description

DescriptionKenvue is currently recruiting for:Assistant Manager - Data EngineeringThis position reports into Manager - Data Engineering and is based at Bangalore.Who We AreAt 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\xc2\xae, AVEENO\xc2\xae, TYLENOL\xc2\xae, LISTERINE\xc2\xae, JOHNSON\'S\xc2\xae and BAND-AID\xc2\xae 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 DoThe position is responsible for:

• Subject Matter Expert for Azure Data, Analytics & AI with experience Azure architecture design preferred. Good understanding of migration and modernization strategies and approaches.

• Helping business migrate and/or build Data, Analytics & AI workloads throughout their Azure journey towards production and expanding the azure infrastructure usage

• Partnering with various Azure Engineering subject matter experts including the project Managers and business team to scope and build customer facing content, modules, tools and proof of concepts

• Staying current on latest Azure/Cloud innovations in order to conduct experiments, drive product improvement, and act as an Azure subject matter trainer for other engineers

• Development, customize and manage integration tools, databases, warehouses and analytical systems with the use of data related instruments/instances

• Create and run complex queries and automation scripts for operational data processing

• Test the reliability and performance of each part of a system and cooperate with the testing team

• Deploying data models into production environments. This entails providing the model with data stored in a warehouse or coming directly from sources, configuring data attributes, managing computing resources, setting up monitoring tools, etc.

• Responsible for setting up tools to view data, generate reports, and create visuals

• Monitoring the overall performance and stability of the system. Adjust and adapt the automated pipeline as data/models/requirements change.

• Mentor and train colleagues where necessary by helping them learn and improve their skills, as well as innovate and iterate on best practices.

• As per organizational & project priority responsibilities can be added later

Key Responsibilities

• 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 captures metrics and operational KPIs for data pipeline quality and performance.

• Responsible for implementing best practices around systems integration, security, performance and data management.

• Empower the business by creating value through the increased adoption of data, data science and business intelligence landscape.

• 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.

• Develop and optimize procedures to "Productionalize" data science models.

• Manage & support large-scale experimentation done by data scientists.

• Design and prototype new approaches and build solutions at scale.

• Research and cultivate in state-of-the-art data engineering methodologies.

• Establish practices of documentation for learnings and knowledge transfer.

• Design and audit reusable packages or libraries

• Understanding of cloud architecture principles and best practices

• Experience in designing end-to-end solutions that meet business requirements and adhere to scalability, reliability, and security standards.

• Familiarity with version control systems like Bitbucket, Jenkins and DevOps practices for CI/CD pipelines.

What We Are Looking ForRequired Qualifications

• Experience in the architecture and design of services using Azure architecture is added advantage

• Azure data engineering certification is must

• Experience in using of Python/ PySpark and/or Scala for data engineering.

• Understanding of data types/ handling of different data models.

• Desirable to have experience with Spark, Kafka, Flask, Python

• Experience with the Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Synapse, Databricks, deployment of Web Application (Azure) is must

• Good scripting and programming skills.

Desired Qualifications

• Preferred Minimum Education: Bachelor of Engineering

• Other: Azure Data Engineering Certification

• Preferred Area of Study: Data Engineering, Databricks

• Preferred Related Industry Experience: Manufacturing & Logistics, IT Service

• Strong expertise in Azure Architect, Databricks, and Azure Data Engineering.

• Proficiency in SQL and PLSQL.

• Experience with DevOps practices.

What\'s In It For You

• Competitive Benefit Package

• Paid Company Holidays, Paid Vacation, Volunteer Time, Summer Fridays & More!

• Learning & Development Opportunities

• Employee Resource Groups

• This list could vary based on location/region

Kenvue is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identify, age, national origin, or protected veteran status and will not be discriminated against on the basis of disability.

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