Haleon
Website:
haleon.com
Company:
https://www.linkedin.com/company/haleon
Seniority: Not Applicable
Industries: Consumer Services
Job details:
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, production‑ready 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:
- Driving compute and storage optimization to improve performance and cost efficiency.
- Ensuring all solutions align with approved architecture patterns, engineering standards, and design principles.
- 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 & hands‑on engineering
- Act as a hands‑on technical leader, combining deep engineering expertise with clear technical judgment and ownership of outcomes.
- Design, build, and operate robust, scalable data solutions that underpin analytics and AI use cases at enterprise scale.
- Take ownership of complex or high‑risk engineering problems, providing authoritative technical direction.
- Ownership of data foundations within a domain / Value Pool
- Lead the delivery of Data Foundations for an assigned Value Pool or domain, building deep understanding of its data, systems, and use cases.
- Own the full data engineering lifecycle within the domain, from ingestion and transformation through to production operation.
- Ensure data assets are reliable, reusable, and fit‑for‑purpose for downstream analytics and AI consumption.
- Data quality, security & governance by design
- Embed data quality, security, and governance controls directly into data engineering solutions rather than treating them as afterthoughts.
- Ensure engineering solutions comply with enterprise standards, data classification, and regulatory requirements.
- Platform efficiency, performance & automation
- Drive compute and storage optimisation, improving performance and cost efficiency across data platforms.
- Design and implement high levels of data platform automation (infrastructure and software) to support stability, scalability, and reliability.
- Ensure solutions align with approved architecture patterns, engineering standards, and platform design principles.
- Engineering standards & organisational quality
- Be part of the team accountable for data engineering quality, consistency, and standards across the organisation.
- Contribute to defining and evolving reusable engineering patterns and best practices.
- Collaboration & mentorship
- Work closely with Data Architects, Solution Architects, Analysts, and Data Scientists to translate business and analytical needs into production‑ready data assets.
- Provide technical guidance and mentoring to Senior Data Engineers and Junior Data Engineers, raising overall engineering capability.
- Support talent development, mentoring, hiring, and technical capability growth.
- Technology evolution & innovation
- Evaluate and introduce new data engineering technologies and approaches where they deliver clear value and align with enterprise standards.
- Balance innovation with platform stability, ensuring changes are sustainable at enterprise scale.
Essential
Qualifications and skills
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 event‑driven 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 data‑focused 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 real‑time and batch (Lambda‑style) architectures.
- Ability to design and implement logging, tracing, and application monitoring systems
- Experience building and maintaining APIs.
Job Posting End Date
2026-08-26
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 execution of our inclusion and belonging programmes that are open to all Haleon employees.
The personal information you provide will be kept confidential, used only for legitimate business purposes, and will never be used in making any employment decisions, including hiring decisions.
Adjustment or Accommodations Request
If you require a reasonable adjustment or accommodation or other assistance to apply for a job at Haleon at any stage of the application process, please let your recruiter know by providing them with a description of specific adjustments you are requesting. We’ll provide all reasonable adjustments to support you throughout the recruitment process and treat all information you provide us in confidence.
Note to candidates
The Haleon recruitment team will contact you using a Haleon email account (@haleon.com). If you are not sure whether the email you received is from Haleon, please get in touch.
Click on Apply to know more.
