Jobs / Haleon / Principal Data Engineer - Commercial Effectiveness

Principal Data Engineer - Commercial Effectiveness

Haleon
Bengaluru Campus 31 Onsite Data Use & Analytics
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About this role

Welcome to Haleon. We’re a purpose-driven, world-class consumer company putting everyday health in the hands of millions. In just three years since our launch, we’ve 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 it’s 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 highperforming data engineering team, setting clear technical direction and delivery standards.

·        Provide handson 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, highquality, and costefficient 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:

o   Driving compute and storage optimization to improve performance and cost efficiency.

o   Ensuring all solutions align with approved architecture patterns, engineering standards, and design principles.

o   Designing 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

o   Act as a handson technical leader, combining deep engineering expertise with clear technical judgment and ownership of outcomes.

o   Design, build, and operate robust, scalable data solutions that underpin analytics and AI use cases at enterprise scale.

o   Take ownership of complex or highrisk engineering problems, providing authoritative technical direction.

·         Ownership of data foundations within a domain / Value Pool

o   Lead the delivery of Data Foundations for an assigned Value Pool or domain, building deep understanding of its data, systems, and use cases.

o   Own the full data engineering lifecycle within the domain, from ingestion and transformation through to production operation.

o   Ensure data assets are reliable, reusable, and fitforpurpose for downstream analytics and AI consumption.

·         Data quality, security & governance by design

o   Embed data quality, security, and governance controls directly into data engineering solutions rather than treating them as afterthoughts.

o   Ensure engineering solutions comply with enterprise standards, data classification, and regulatory requirements.

·         Platform efficiency, performance & automation

o   Drive compute and storage optimisation, improving performance and cost efficiency across data platforms.

o   Design and implement high levels of data platform automation (infrastructure and software) to support stability, scalability, and reliability.

o   Ensure solutions align with approved architecture patterns, engineering standards, and platform design principles.

·         Engineering standards & organisational quality

o   Be part of the team accountable for data engineering quality, consistency, and standards across the organisation.

o   Contribute to defining and evolving reusable engineering patterns and best practices.

·         Collaboration & mentorship

o   Work closely with Data Architects, Solution Architects, Analysts, and Data Scientists to translate business and analytical needs into productionready data assets.

o   Provide technical guidance and mentoring to Senior Data Engineers and Junior Data Engineers, raising overall engineering capability.

o   Support talent development, mentoring, hiring, and technical capability growth.

·         Technology evolution & innovation

o   Evaluate and introduce new data engineering technologies and approaches where they deliver clear value and align with enterprise standards.

o   Balance innovation with platform stability, ensuring changes are sustainable at enterprise scale.

 

Qualifications and skills

 

Essential

 

We are looking for professionals with these required skills to achieve our goals: 

·         Minimum 15 years as a full-time data engineer or software engineer 

·         Have proven experience of building data solutions for the [Commercial Effectiveness, Supply Chain Excellence, Innovation, Corporate Functions] Value Pool and the associated data domains.

·         Bachelor’s degree in engineering, Mathematics, Statistics, or Computer Science 

·         Deep experience with Continuous Improvement tools 

·         Deep experience working with data to extract, transform, and load processes and controls 

 

Preferred

If you have the following characteristics, it would be a plus:

·        Experience building and operating GxP-regulated technology in Healthcare

·        5+ years utilizing Agile Product Management- Scrum and SAFe methodologies

·        Strong stakeholder management experience.

·        Expertise with Data Engineering or Site Reliability Engineering

·        Minimum 6 years working on Big Data platforms, preferably Spark based.

·        Minimum 6 years deploying solutions on Cloud Platforms, preferably Azure or GCP

·        Distributed compute technologies such as Databricks and Apache Spark, with solid understanding of underlying programming frameworks.

·        Streaming and eventdriven architectures, using technologies such as Kafka and Azure Event Hubs.

·        Cloud storage solutions including Azure Data Lake Storage and Blob Storage.

·        Azure Synapse Analytics and modern cloud data warehousing patterns.

·        Azure Functions and related datafocused platform services.

·        Infrastructure as Code and automated delivery using tools such as Azure DevOps, Terraform, Ansible, or equivalents.

·        Containerized deployment platforms, including Azure Kubernetes Service (AKS).

·        Workflow orchestration and scheduling tools such as Apache Airflow.

·        Fluency in Agile and DevOps practices, including CI/CD and automation.

·        Strong understanding of data streaming patterns, including hybrid realtime and batch (Lambdastyle) architectures.

·        Ability to design and implement logging, tracing, and application monitoring systems

·        Experience building and maintaining APIs.

 

 

 

 Job Posting End Date

 

 

2026-05-31

 

 

 

Equal Opportunities

Haleon are committed to mobilising our purpose in a way that represents the diverse consumers and communities who rely on our brands every day. It guides us in creating an inclusive culture, where different backgrounds and views are valued and respected – all in support of understanding and best serving the needs of our consumers and unleashing the full potential of our people. It’s important to us that Haleon is a place where all our employees feel they truly belong.

During the application process, we may ask you to share some personal information, which is entirely voluntary. This information ensures we meet certain regulatory and reporting obligations and supports the development, refinement, and exe

About Haleon

Consumer healthcare company spun off from GSK, making brands like Sensodyne, Advil, and Centrum. Based in Weybridge, UK.

haleon.com

Job Details
LocationBengaluru Campus 31
Work typeOnsite
DepartmentData Use & Analytics
SenioritySenior
CountryIndia
About the company
Haleon
Consumer healthcare company spun off from GSK, making brands like Sensodyne, Advil, and Centrum. Based in Weybridge, UK.
View all 402 open jobs at Haleon
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