Analytics Engineer

Analytics Engineer

O que fazemos

At Kenvue, percebemos o extraordinário poder do cuidado diário. Construída com base em mais de um século de herança e enraizada na ciência, somos a casa de marcas icônicas - incluindo NEUTROGENA®, AVEENO®, TYLENOL,® LISTERINE,® JOHNSON'S® e BAND-AID® que você já conhece e ama. A ciência é a nossa paixão; O cuidado é o nosso talento.

Quem somos

Nossa equipe global é de ~ 22.000 pessoas brilhantes com uma cultura no local de trabalho onde cada voz é importante e cada contribuição é apreciada. Somos apaixonados por insights, inovação e comprometidos em entregar os melhores produtos aos nossos clientes. Com experiência e empatia, ser um Kenvuer significa ter o poder de impactar milhões de pessoas todos os dias. Colocamos as pessoas em primeiro lugar, nos importamos ferozmente, ganhamos confiança com a ciência e resolvemos com coragem - e temos oportunidades brilhantes esperando por você! Junte-se a nós para moldar nosso futuro - e o seu. Para obter mais informações, clique em aqui.

Role reporta para:

Senior Manager - Forecasting & Analytics

Localização:

Asia Pacific, India, Karnataka, Bangalore

Local de trabalho:

Híbrido

O que você fará

Job Overview

We are looking for a Analytics Engineer with 4+ years of experience to help build and optimize our next-generation data platform using Microsoft Fabric. You will be responsible for designing scalable data pipelines, managing Lakehouse/Warehouses, and ensuring our data architecture supports a "Plug-and-Play" model for downstream business projects. The ideal candidate is a hands-on engineer who can translate complex data requirements into efficient, governed, and reusable data assets.

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Key Responsibilities

1. Fabric Ecosystem Engineering

· End-to-End Pipeline Development: Design and implement data ingestion and transformation workflows using Fabric Data Factory (Pipelines & Dataflows Gen2).

· Lakehouse & Warehouse Management: Architect and maintain OneLake storage structures, including Lakehouse (Delta Parquet) and Data Warehouse environments, to ensure a single source of truth.

· KPI Hub Integration: Contribute to the development of the centralized KPI Hub by building reusable datasets that reduce data redundancy across the enterprise.

2. Data Modeling & Transformation

· Advanced Spark/Python: Utilize Fabric Notebooks and PySpark for complex data engineering tasks, optimization, and large-scale processing.

· Semantic Layer Design: Build and optimize Power BI Semantic Models (Direct Lake mode) to provide high-performance reporting capabilities without data duplication.

· Data Quality & Governance: Implement automated data validation checks and metadata management to ensure compliance with GxP, SOX, and PII standards.

3. Automation & Platform Operations

· Fabric CI/CD: Implement version control and deployment automation for Fabric items using Git integration and deployment pipelines.

· Cost & Performance Optimization: Monitor capacity utilization and optimize queries/storage to ensure the platform remains cost-efficient.

· Technical Documentation: Create detailed data lineage maps, schema definitions, and deployment runbooks to support team collaboration.

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Required Qualifications

· Experience: 4+ years of total experience in Data Engineering, with at least 1 year of hands-on experience in Microsoft Fabric or deep expertise in the Azure Data Stack (Lakeshouse, Data Factory, Databricks).

· Technical Proficiency:

o Strong SQL and PySpark skills for data manipulation.

o Hands-on experience with Delta Lake and Parquet formats.

o Experience with Power BI and DAX is highly preferred.

· Cloud Knowledge: Firm understanding of Azure networking, security (Managed Identities, Service Principals), and Entra ID (Azure AD) integration.

· Problem Solving: Ability to work in a fast-paced environment and deliver scalable solutions that align with a broader Solution Architecture.

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Desired Qualifications

· Certification: DP-600 (Microsoft Fabric Analytics Engineer Associate) is a significant plus.

· Architectural Mindset: Familiarity with broader solution architecture principles is a strong plus.

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