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Data Engineer

Hello. We’re Haleon. A new world-leading consumer health company. Shaped by all who join us. Together, we’re improving everyday health for billions of people. By growing and innovating our global portfolio of category-leading brands – including Sensodyne, Panadol, Advil, Voltaren, Theraflu, Otrivin, and Centrum – through a unique combination of deep human understanding and trusted science. What’s more, we’re achieving it in a company that we’re in control of. In an environment that we’re co-creating. And a culture that’s uniquely ours. Care to join us. It isn’t a question.

With category leading brands such as Sensodyne, Voltaren and Centrum, built on trusted science and human understanding, and combined with our passion, knowledge and expertise, we’re uniquely placed to do this and to grow a strong, successful business.

This is an exciting time to join us and help shape the future. It’s an opportunity to be part of something special.

About the role

You will be working on the latest data platform technologies, and a part of a high-performing team fully committed to employee growth and development. If you’re a skilled engineer who wants to build using the latest technology and acquire new skills in data and analytics, then come join our team.

You will be integrating components, designing frameworks, and building reusable data solutions for Haleon’s Enterprise Data & Analytics Platform. You will enable faster acquisition, ingestion, and curation of analytical-ready datasets.

This is very hands-on development role which includes developing & delivering code through from origin to production, plus working in partnership with 3rd party development service providers to help ensure that code comes in on time, to quality and in line with the overall ecosystem being established.

The Data Engineer will directly contribute to the extensive and varied build and deployment activities involved in establishing the new platform then continue to work on the already significant and growing pipeline of future buildouts of platform services on the Enterprise Data & Analytics Platform.

Key responsibilities

Development

  • Hands on, sleeves up development and delivery code through from origin to production, plus working in partnership with 3rd party development service providers to help ensure that performant/quality code comes is written and in line with the overall ecosystem being established

  • The Data Engineer will directly contribute to the extensive and varied build and deployment activities involved in establishing the new products/platform then continue to work on the already significant and growing pipeline of future buildouts of platform services on the Enterprise Data & Analytics Platform.

Qualifications and Essential Skills

  • MS/BS degree in Computer Science, Engineering, Data Science or equivalent experience, with preference on experience and proven track record. Ideal candidate would have an impressive hands-on work history in an advanced, recognized, and innovative environment.   
  • 4+ years of Data engineering experience and seasoned coder in the relevant languages: Pyspark, SQL, etc
  • 4+ years of experience with the Azure data and analytics stack: Azure Databricks, Azure Data Factory (SHIR, etc), Keyvault, LogicApp, Unity Catalog (UC), ADLS Gen2, Synapse, etc.
  • Experience with Agile (in a highly structured and robust reporting delivery management methodology format) delivery frameworks and tools: SAFe, Jira, Confluence, Github Action and Azure DevOps (Pipelines, self-hosted agent, etc), Github, delivery break down estimation, etc.
  • Fully conversant with big-data processing approaches and “schema-on-read” methodologies. Preference for deep understanding of Spark, Databricks and Delta Lake, and applying them to solve data science and machine learning business problems.
  • Fluency with Data/Platform/Reliability Engineering patterns for operational resilience & co-contribution development patterns.
  • Ability to develop and optimise the Spark code for large volumes of Data.
  • Familiar deploying enterprise analytics solutions at scale with applicable services: administration, qualification, and user access provisioning.  
  • Experience articulating business value of analytics projects and progressing solutions from MVP to scaled-up production solutions.
  • Production experience delivering CI/CD pipelines across Azure and vendor products.
  • Knowledge of Data modelling, Purview and their application. 
  • Ability to work in close partnership with groups across the IT organization (security, compliance, infrastructure, etc.) and business stakeholders in the commercial organizations. 
  • Ability to develop and maintain productive working relationships with suppliers and specialist technology providers to assemble and maintain a distinctive and flexible mix of capabilities against future requirements.  
  • Ideal candidate possesses great communication skills and the ability to communicate inherently complicated technical concepts to non-technical stakeholders of all levels.

Good To Have Skills

  • Knowledge of Microsoft Fabric, PowerBI, PowerApp, Azure Synapse, Purview and Scala.
  • Experience with visualization tools and their application: developing reports, dashboards and KPI scorecards.

Delivery

  • Ensure project goals are achieved on time in alignment with the stakeholders’ expectation.

  • Ability to work on complex projects and in a distributed environment.

  • Escalate when necessary and in a timely manner.

  • Work in close collaboration with other team members in the Enterprise Data & Analytics Platform team, to ensure Development/Delivery aspects are well represented in the project’s requirements and deliverables. 

Methodology

  • Incorporate agile ways of working into the delivery process utilising DABL (Discovery, Alpha, Beta, Launch)

  • Individuals will work as part of product-centric delivery team(s) that will focus on delivering value independently while fully embracing integrated DevOps approaches. 

Ownership

  • Take ownership for the delivery/development projects and help steer until completion

Governance

  • Maintain governance that allows projects and stakeholders to manage overall project performance and manage programme risks within the global nature of some of the programmes. 

Forward looking

  • Remain flexible towards technology approaches to ensure we are taking advantage of new technologies. 

  • Keep abreast of industry developments in analytics and be able to interpret how these would impact services and present new opportunities. 

Quality, Risk & Compliance

  • Ensure all risk and issues associated with owned projects are recorded and managed in the appropriate Risk & Issue logs in a timely manner.

  • Ensure all Risks and Issues have clear action/mitigation/contingency plans defined, with named action owners and timelines for completion. 

Technical Architecture

  • Be conversant with technical architecture to contribute to design discussions in partnership with the Delivery/Development Lead and dedicated Analytics & Data Architect. 

Care to join us. Find out what life at Haleon is really like www.haleon.com/careers/

At Haleon we embrace our diverse workforce by creating an inclusive environment that celebrates our unique perspectives, generates curiosity to create unmatched understanding of each other, and promotes fair and equitable outcomes for everyone. We're striving to create a climate where we celebrate our diversity in all forms by treating each other with respect, listening to different viewpoints, supporting our communities, and creating a workplace where your authentic self belongs and thrives. We believe in an agile working culture for all our roles. If flexibility is important to you, we encourage you to explore with our hiring team what the opportunities are.

As you apply, we will ask you to share some personal information, which is entirely voluntary. We want to have an opportunity to consider a diverse pool of qualified candidates and this information will assist us in meeting that objective and in understanding how well we are doing against our inclusion and diversity ambitions. We would really appreciate it if you could take a few moments to complete it. Rest assured, Hiring Managers do not have access to this information and we will treat your information confidentially.

Haleon is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment without regard to race, color, national origin, religion, sex, pregnancy, marital status, sexual orientation, gender identity/expression, age, disability, genetic information, military service, covered/protected veteran status or any other federal, state or local protected class.

Accommodation Requests

If you require a reasonable 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 accommodations you are requesting. We’ll provide all reasonable accommodations to support you throughout the recruitment process and treat all information you provide us in confidence.

Average salary estimate

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What You Should Know About Data Engineer, GSKNCH

Hey there! We’re Haleon, a revolutionary consumer health company dedicated to improving the everyday health of billions of people worldwide. With an impressive portfolio of well-loved brands like Sensodyne, Panadol, and Voltaren, we're on a mission to grow and innovate through a blend of deep human insight and trusted science. Right now, we're on the lookout for a Data Engineer to join our fantastic team in Bengaluru. In this role, you’ll tap into the latest data platform technologies while working closely with a high-performing crew that prioritizes your growth and development. If you're passionate about building remarkable data solutions and gaining new analytical skills, this is your chance to shine! As a Data Engineer, you’ll be responsible for integrating components and designing frameworks for our Enterprise Data & Analytics Platform. The work is hands-on and involves delivering high-quality code from start to finish, collaborating with third-party providers to ensure timely delivery. Your role will be pivotal in establishing the new platform and its future enhancements. We’re looking for someone with significant coding experience, ideally with a background in Azure data tools. If you have 4+ years in data engineering, are proficient in languages like Pyspark and SQL, and have a flair for communicating complex ideas simply, we want to hear from you! Embrace this exciting journey with us and help shape a healthier tomorrow!

Frequently Asked Questions (FAQs) for Data Engineer Role at GSKNCH
What are the main responsibilities of a Data Engineer at Haleon?

As a Data Engineer at Haleon, your main responsibilities include integrating components, designing frameworks, and building reusable data solutions for our Enterprise Data & Analytics Platform. You'll be working hands-on with the latest technology to develop and deliver code through its entire lifecycle, from origin to production, while collaborating closely with third-party development providers to ensure quality output.

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What qualifications do I need for the Data Engineer position at Haleon?

To qualify for the Data Engineer position at Haleon, you should ideally hold an MS or BS degree in Computer Science, Engineering, Data Science, or equivalent experience. Additionally, candidates should have at least 4 years of data engineering experience, with proficiency in relevant coding languages like Pyspark and SQL, as well as experience with the Azure data and analytics stack.

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What skills are essential for a Data Engineer at Haleon?

Essential skills for the Data Engineer role at Haleon include a strong command of data engineering languages such as Pyspark and SQL, familiarity with Azure tools like Databricks and Data Factory, and an understanding of Agile methodologies. Also important are your abilities in big data processing, developing CI/CD pipelines, and effective communication with both technical and non-technical stakeholders.

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What is the company culture like at Haleon for Data Engineers?

At Haleon, the culture is all about inclusivity, collaboration, and growth. We celebrate diversity and aim to create an environment where everyone thrives. As a Data Engineer, you'll find a supportive team that encourages innovation and professional development while working together to improve health outcomes globally.

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How does Haleon support the career growth of Data Engineers?

Haleon believes in nurturing talent and fostering career growth for Data Engineers through continuous learning, feedback, and hands-on experience with cutting-edge technologies. The company promotes an agile work culture, allowing team members the flexibility to develop their skills while contributing to impactful projects that enhance health for millions.

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Common Interview Questions for Data Engineer
Can you explain your experience with Azure data and analytics tools relevant to the Data Engineer role?

When answering this question, provide specific examples of your experience with Azure tools such as Databricks, Azure Data Factory, and Synapse. Describe projects where you've successfully implemented these technologies to solve complex data problems, highlighting the impact of your work on business outcomes.

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How do you ensure code quality in your development process as a Data Engineer?

Discuss your approach to ensuring code quality, such as incorporating unit testing, code reviews, and using best practices in coding standards. Mention specific tools like Azure DevOps and GitHub Actions that you have utilized for continuous integration and deployment to maintain high code quality.

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Describe a challenging data engineering project you worked on. What were the challenges and how did you overcome them?

In your response, outline the project scope, the specific challenges faced, and the strategies you employed to overcome them. Highlight problem-solving approaches, teamwork, and any innovations you introduced to achieve successful project outcomes.

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How familiar are you with schema-on-read methodologies?

Explain your understanding of schema-on-read, including its advantages over schema-on-write in data processing. Provide instances where you’ve applied this methodology to facilitate quick dataset access and flexibility in data analysis.

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Can you discuss your experience with big data processing using Spark?

Share details about your experience with Apache Spark, focusing on projects where you processed large datasets. Highlight the techniques you used and how you optimized Spark code for efficiency, as well as your understanding of performance tuning.

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How have you collaborated with cross-functional teams in previous roles?

Discuss your experience working with different teams, such as IT, business stakeholders, and data scientists. Provide examples of successful collaborations, emphasizing communication, shared goals, and any frameworks you used (like Agile) to facilitate teamwork.

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What strategies do you use for effective data lineage and governance?

Outline your strategies for maintaining data lineage and governance. Discuss tools and practices you have employed to ensure data integrity and compliance, such as Azure Purview and regular audits, as well as how you communicate these practices to stakeholders.

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What are your thoughts on the role of DevOps in data engineering?

Express your perspective on how integrating DevOps principles into data engineering enhances collaboration, reduces silos, and enables rapid delivery of data solutions. Share any experiences where you implemented DevOps practices in your previous roles.

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How do you stay updated with the latest trends in data engineering?

Discuss your proactive approach to staying informed, such as following industry blogs, attending conferences, participating in online communities, and leveraging platforms like LinkedIn to connect with thought leaders in data engineering.

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Can you describe your approach to delivering data solutions that align with business needs?

Detail your approach to gathering business requirements, including working closely with stakeholders to understand their needs. Discuss how you translate those requirements into actionable data engineering tasks that effectively support business objectives.

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DATE POSTED
April 9, 2025

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