Business Intelligence Engineer

Job description

Kenvue is currently recruiting for a: Business Intelligence Engineer What we do 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® that you already know and love. Science is our passion; care is our talent. Who We Are Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated.  We are 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 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: Regional Engagement Lead Location: Asia Pacific, India, Karnataka, Bangalore Work Location: Hybrid What you will do The Business Intelligence Engineer will design, develop, and maintain advanced analytics solutions to support Supply Chain and business decision-making. This role focuses on building and optimizing Power BI dashboards, managing SQL-based data flows (front-end and back-end), and integrating data from SAP, Databricks, and modern platforms such as Microsoft Fabric. The ideal candidate will combine strong technical expertise with deep understanding of supply chain processes to deliver scalable, automated, and insightful analytics solutions.   Key Responsibilities 1. Develop and Maintain BI Solutions for Supply Chain: ·       Design, build, and optimize Power BI dashboards focused on supply chain KPIs (OTIF, Cost to Serve, Inventory, Transportation, Customer Experience). ·       Ensure data accuracy and integrity across dashboards and reports. ·       Train supply chain stakeholders on effective use of BI tools and dashboards.   2. Data Engineering and Automation: ·       Develop and maintain SQL queries, stored procedures, and ETL pipelines for supply chain data preparation and transformation. ·       Automate data flows and reporting processes to improve efficiency and reduce manual effort. ·       Implement best practices for data governance and security across supply chain datasets. 3. Integration and Advanced Analytics: ·       Integrate data from SAP, Databricks, and other enterprise systems into centralized supply chain data models. ·       Leverage Microsoft Fabric and cloud technologies for scalable analytics solutions. ·       Collaborate with supply chain analysts and planners to enable predictive analytics (e.g., demand forecasting, inventory optimization). 4. Continuous Improvement and Innovation: ·       Identify opportunities for process automation and analytics enhancements within supply chain operations. ·       Stay updated on emerging BI and supply chain technologies and recommend adoption where relevant. ·      Participate in workshops and cross-functional projects to align analy