Analytics Engineer

Analytics Engineer

Lo que hacemos

En Kenvue, nos damos cuenta del extraordinario poder del cuidado diario. Sobre la base de más de un siglo de herencia y arraigados en la ciencia, somos el hogar de marcas icónicas, incluidas NEUTROGENA®, AVEENO,® TYLENOL,® LISTERINE,® JOHNSON'S® y BAND-AID® que ya conoces y amas. La ciencia es nuestra pasión; El cuidado es nuestro talento.

Quiénes somos

Nuestro equipo global está formado por ~ 22.000 personas brillantes con una cultura laboral en la que cada voz importa y cada contribución es apreciada. Nos apasionan las ideas, innovación y comprometidos con la entrega de los mejores productos a nuestros clientes. Con experiencia y empatía, ser un Kenvuer significa tener el poder de impactar a millones de personas todos los días. Ponemos a las personas en primer lugar, nos preocupamos ferozmente, nos ganamos la confianza de la ciencia y resolvemos con coraje, ¡y tenemos oportunidades brillantes esperándote! Únase a nosotros para dar forma a nuestro futuro y al suyo. Para obtener más información, haga clic en aquí.

Role reports to:

Senior Manager - Forecasting & Analytics

Ubicación:

Asia Pacific, India, Karnataka, Bangalore

Lugar de trabajo:

Híbrido

What will you

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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