At a Glance
- Tasks: Design and implement data architectures to support cutting-edge AI and machine learning workflows.
- Company: Join GSK, a global biopharma leader dedicated to advancing health through innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact in medical discovery while working with top-tier talent and technology.
- Qualifications: 5+ years in data architecture and experience with big data platforms required.
- Other info: Collaborative environment focused on innovation and career development.
The predicted salary is between 48000 - 72000 ÂŁ per year.
The Onyx Research Data Tech organization is GSK’s Research data ecosystem which has the capability to bring together, analyze, and power the exploration of data at scale. We partner with scientists across GSK to define and understand their challenges and develop tailored solutions that meet their needs. The goal is to ensure scientists have the right data and insights when they need it to give them a better starting point for and accelerate medical discovery. Ultimately, this helps us get ahead of disease in more predictive and powerful ways.
Onyx is a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data/metadata/knowledge platforms, and AI/ML and analysis platforms, all geared toward:
- Building a next-generation, metadata- and automation-driven data experience for GSK’s scientists, engineers, and decision-makers, increasing productivity and reducing time spent on “data mechanics”.
- Providing best-in-class AI/ML and data analysis environments to accelerate our predictive capabilities and attract top-tier talent.
- Aggressively engineering our data at scale, as one unified asset, to unlock the value of our unique collection of data and predictions in real-time.
The Onyx Data Architecture team sits within the Data Engineering team, which is responsible for the design, delivery, support, and maintenance of industrialized automated end-to-end data services and pipelines. They apply standardized data models and mapping to ensure data is accessible for end users in end-to-end user tools through the use of APIs. They define and embed best practices and ensure compliance with Quality Management practices and alignment to automated data governance. They also acquire and process internal and external, structured and unstructured data in line with Product requirements.
As a Data Architect II, you'll apply your expertise in big data and AI/GenAI workflows to support GSK's complex, regulated R&D environment. You'll contribute to designing Data Mesh/Data Fabric architectures while enabling modern AI and machine learning capabilities across our platform.
You will be responsible for:
- Partnering with the Scientific Knowledge Engineering team to develop physical data models to build fit-for-purpose data products.
- Designing data architecture aligned with enterprise-wide standards to promote interoperability.
- Collaborating with the platform teams and data engineers to maintain architecture principles, standards, and guidelines.
- Designing data foundations that support GenAI workflows including RAG (Retrieval-Augmented Generation), vector databases, and embedding pipelines.
- Working across business areas and stakeholders to ensure consistent implementation of architecture standards.
- Leading reviews and maintaining architecture documentation and best practices for Onyx and our stakeholders.
- Adopting security-first design with robust authentication and resilient connectivity.
- Providing best practices and leadership, subject matter, and GSK expertise to architecture and engineering teams composed of GSK FTEs, strategic partners, and software vendors.
Basic Qualifications:
We are looking for professionals with these required skills to achieve our goals:
- Bachelor’s degree in computer science, engineering, Data Science or similar discipline.
- 5+ years of experience in data architecture, data engineering, or related fields in pharma, healthcare, or life sciences R&D.
- 3+ years’ experience of defining architecture standards, patterns on Big Data platforms.
- 3+ years’ experience with data warehouse, data lake, and enterprise big data platforms.
- 3+ years’ experience with enterprise cloud data architecture (preferably Azure or GCP) and delivering solutions at scale.
- 3+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
Preferred Qualifications:
If you have the following characteristics, it would be a plus:
- Master's or PhD in computer science, engineering, Data Science or similar discipline.
- Deep knowledge and use of at least one common programming language: e.g., Python, Scala, Java.
- Experience with AI/ML data workflows: feature stores, vector databases, embedding pipelines, model serving architectures.
- Familiarity with GenAI/LLM data patterns: RAG architectures, prompt engineering data requirements, fine-tuning data preparation.
- Experience with GCP data/analytics stack: Spark, Dataflow, Dataproc, GCS, Bigquery.
- Experience with enterprise data tools: Ataccama, Collibra, Acryl.
- Experience with Agile frameworks: SAFe, Jira, Confluence, Azure DevOps.
- Experience applying CI/CD principles to data solutions.
- Experience with Spark and RAG-based architectures for data science and ML use cases.
- Strong communication skills—ability to explain technical concepts to non-technical stakeholders.
- Pharmaceutical, healthcare, or life sciences background.
GSK is a global biopharma company with a purpose to unite science, technology and talent to get ahead of disease together. We aim to positively impact the health of 2.5 billion people by the end of the decade, as a successful, growing company where people can thrive. We get ahead of disease by preventing and treating it with innovation in specialty medicines and vaccines. We focus on four therapeutic areas: respiratory, immunology and inflammation; oncology; HIV; and infectious diseases – to impact health at scale.
People and patients around the world count on the medicines and vaccines we make, so we’re committed to creating an environment where our people can thrive and focus on what matters most. Our culture of being ambitious for patients, accountable for impact and doing the right thing is the foundation for how, together, we deliver for patients, shareholders and our people.
GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
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.
Data Architect II in Stevenage employer: Gsk
Contact Detail:
Gsk Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect II in Stevenage
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with GSK employees on LinkedIn. A personal touch can make all the difference when it comes to landing that interview.
✨Tip Number 2
Prepare for those interviews by brushing up on your technical skills and understanding GSK's mission. We want to see how you can contribute to our goals, so be ready to discuss your experience with data architecture and AI workflows.
✨Tip Number 3
Showcase your problem-solving skills! During interviews, share specific examples of how you've tackled challenges in data engineering or architecture. We love hearing about real-world applications of your expertise.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining our team at GSK.
We think you need these skills to ace Data Architect II in Stevenage
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Architect II role. Highlight your experience in data architecture, big data platforms, and any relevant projects that showcase your skills. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your expertise can contribute to our mission at GSK. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to highlight your technical skills, especially those related to AI/ML workflows and cloud data architecture. Mention specific tools and technologies you’ve worked with, as this will help us understand your fit for the team.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s straightforward and ensures your application goes directly to us. Plus, you’ll find all the details you need about the role there!
How to prepare for a job interview at Gsk
✨Know Your Data Architecture Inside Out
Before the interview, make sure you’re well-versed in data architecture principles, especially those relevant to big data and AI workflows. Brush up on your knowledge of data mesh and data fabric architectures, as these are key components of the role.
✨Showcase Your Collaboration Skills
Since this position involves working closely with various teams, be prepared to discuss past experiences where you successfully collaborated with others. Highlight how you’ve partnered with stakeholders to develop data solutions that meet their needs.
✨Prepare for Technical Questions
Expect technical questions related to data engineering and architecture standards. Review common programming languages like Python or Scala, and be ready to explain your experience with cloud data architecture, particularly Azure or GCP.
✨Demonstrate Your Problem-Solving Abilities
Think of specific examples where you’ve tackled complex data challenges. Be ready to discuss how you approached these problems, the solutions you implemented, and the impact they had on your team or project.