Principal Data Engineer - Commercial Effectiveness (Bellandur)

Welcome to Haleon. Were a purpose-driven, world-class consumer company putting everyday health in the hands of millions. In just three years since our launch, weve grown, evolved and are now entering an exciting new chapter one filled with bold ambitions and enormous opportunity. Our trusted portfolio of brands including Sensodyne, Panadol, Advil, Voltaren, Theraflu, Otrivin, and Centrum lead in resilient and growing categories. What sets us apart is our unique blend of deep human understanding and trusted science. Now its time to fully realise the full potential of our business and our people. We do this through our Win as One strategy. It puts our purpose to deliver better everyday health with humanity at the heart of everything we do. It unites us, inspires us, and challenges us to be better every day, driven by our agile, performance-focused culture. As a Principal Data Engineer, you will drive a team to design, build, and operate robust, scalable data solutions that directly enable analytics and AI use cases across the business. You will lead the data foundation delivery for the (Commercial Effectiveness, Supply Chain Excellence, Innovation, or Corporate Functions) Value Pool, will take ownership across the full data engineering lifecycle and will build a deep understanding of your respective domain. You will apply strong data modelling practices, optimize performance, and drive automation, while embedding data quality, security, and governance controls into all solutions. Working closely with architects, analysts, and data scientists, you will translate business and analytical requirements into reliable, productionready data assets. The role sits within the Data Architecture and Engineering team in the Data and AI Office. Key responsibilities Operate as a manager , bringing strong technical depth, clear engineering judgment, and ownership of outcomes. Lead and develop a high performing data engineering team , setting clear technical direction and delivery standards. Provide hands on technical leadership while maintaining accountability for quality, performance, and outcomes. Own delivery across assigned Value Pools, managing prioritisation, capacity, and dependencies . Drive consistent adoption of engineering standards, architecture patterns, and best practices . Foster a strong DevOps and automation culture , including CI/CD, IaC, and operational excellence. Ensure teams deliver secure, high quality, and cost efficient data solutions. Collaborate with architecture, product, and governance teams to align delivery with enterprise data and AI strategy . Apply specialist data engineering expertise to work effectively with both business and technical stakeholders, translating requirements into robust engineering solutions. Design, build, and evolve reusable, scalable data assets within an assigned Value Pool, contributing directly to analytics and AI use cases. Contribute to a team accountable for data engineering quality, consistency, and standards across the organization. This includes: oDriving compute and storage optimization to improve performance and cost efficiency. oEnsuring all solutions align with approved architecture patterns, engineering standards, and design principles . oDesigning and implementing high levels of platform automation (infrastructure and software) to support operational stability, scalability, and reliability. Provide thought leadership in data engineering, data management, and analytics, leveraging deep technical expertise and strong collaboration skills to drive business value. Technical leadership & handson engineering oAct as a hands on technical leader , combining deep engineering expertise with clear technical judgment and ownership of outcomes. oDesign, build, and operate robust, scalable data solutions that underpin analytics and AI use cases at enterprise scale. oTake ownership of complex or highrisk engineering problems, providing authoritative technical direction . Ownership of data foundations within a domain / Value Pool oLead the delivery of Data Foundations for an assigned Value Pool or domain, building deep understanding of its data, systems, and use cases. oOwn the full data engineering lifecycle within the domain, from ingestion and transformation through to production operation. oEnsure data assets are reliable, reusable, and fit for purpose for downstream analytics and AI consumption. Data quality, security & governance by design oEmbed data quality, security, and governance controls directly into data engineering solutions rather than treating them as afterthoughts. oEnsure engineering solutions comply with enterprise standards, data classification, and regulatory requirements . Platform efficiency, performance & automation oDrive compute and storage optimisation , improving performance and cost efficiency across data .