At a Glance
- Tasks: Lead the architectural direction of a large-scale data transformation programme.
- Company: Join a forward-thinking tech company with a focus on data innovation.
- Benefits: Enjoy a hybrid work model, competitive salary, and professional growth opportunities.
- Other info: Collaborative environment fostering innovation and career advancement.
- Why this job: Shape the future of data architecture and influence key technology decisions.
- Qualifications: Proven experience as a Principal Data Architect with expertise in Apache Spark.
The predicted salary is between 80000 - 100000 £ per year.
Location: Nottingham or London
Working Model: Hybrid — 3 days per week in office
About the Role
UST is seeking a Principal Data Architect to define and drive the architectural direction of a large-scale, complex data transformation programme. This is a senior, influence-led role, not a hands-on engineering position, for a recognised technical authority who shapes strategy, builds consensus, and raises the architectural bar across a multi-disciplinary data organisation.
You will own the end-to-end data architecture across the full data lifecycle: from real-time ingestion and high-quality data capture, through large-scale distributed processing, structured storage and Data LakeHouse design, to curated consumption by Data Scientists, Analysts, Engineers and AI/ML platforms. Spark and distributed data processing sit at the heart of this architecture; deep fluency in these domains is essential.
What You’ll Do:
- Architectural Leadership
- Define and evolve the enterprise data architecture strategy, with a primary focus on Cloud-scale Distributed Data Processing using Apache Spark and PySpark at the core of the platform.
- Establish and maintain architectural artefacts, reference architectures, Architecture Decision Records (ADRs), technical standards, and architecture roadmaps, for the distributed data processing and storage domain.
- Lead architectural governance across the Data LakeHouse, streaming pipelines, and Data Products, ensuring scalability, performance, and engineering excellence are embedded by design.
- Drive simplification and standardisation across the architecture, promoting reuse of proven patterns, appropriate SaaS solutions, and Enterprise platform capabilities.
- Stakeholder Influence & Collaboration
- Influence and align senior stakeholders, internal customers, and Enterprise partners on key technology decisions and the architectural direction of the data ecosystem.
- Partner with Product Management, Engineering, Cyber, and the broader Architecture community to solve complex data challenges and unlock business value.
- Serve as a passionate advocate for the data platform, driving awareness, adoption, and usage aligned to Enterprise architecture standards and patterns.
- Engage actively with UK and Enterprise Architecture groups, contributing to cross-domain standards and architectural thinking.
- Architecture Excellence & Culture
- Nurture architectural excellence within the Data team by leading technical design reviews, setting best practices, and coaching Engineers, Data Scientists, and Analysts on sound architecture principles.
- Foster a culture of innovation within the data platform, identifying opportunities to leverage emerging technologies, including Generative and Agentic AI, within the architecture and development lifecycle.
- Champion data-driven thinking across the wider organisation, supporting the evolution of a scalable, data-led culture.
What You’ll Bring:
Essential Experience & Expertise
- Demonstrable track record as a Principal, Lead, or Senior Data Architect in a large, complex, data-led organisation, operating at an influence and strategy level rather than hands-on delivery.
- Expert-level understanding of Apache Spark and PySpark as the foundation of distributed data processing architectures, including tuning, optimisation, and enterprise-scale deployment patterns.
- Deep expertise in designing and evolving Data LakeHouse architectures, covering ELT pipeline design, structured/semi-structured data processing, partitioning strategies, and Data Product delivery.
- Strong command of workflow orchestration at scale using Apache Airflow or equivalent, integrated with Spark-based processing pipelines.
- Proven expertise in Streaming Data and Event-Driven Architecture design, enabling real-time data flows at enterprise scale.
- Hands-on architectural experience with AWS data services, including AWS Glue (Spark-based ETL), Serverless compute, DynamoDB, S3-based Lake architectures, and associated security and governance tooling.
- Working knowledge of ML and Generative AI platform architecture, including the design of Agentic AI systems within the data and software development lifecycle.
Leadership & Communication
- Exceptional communication skills, able to articulate complex technical architecture to senior business stakeholders and translate business strategy into actionable data architecture decisions.
- A natural collaborator and influencer, able to build consensus across technical, product, and executive communities without direct authority.
- Experience embedding and scaling architectural thinking within large Enterprise settings, elevating the capability of multi-disciplinary data teams.
- Proficiency in software engineering principles, CI/CD practices, and DevOps culture as they apply to data platform delivery.
Principal Data Architect in Nottingham employer: UST
UST is an exceptional employer that fosters a culture of innovation and collaboration, making it an ideal place for a Principal Data Architect to thrive. With a hybrid working model in vibrant locations like Nottingham and London, employees benefit from a supportive environment that prioritises professional growth and architectural excellence. UST encourages continuous learning and offers opportunities to engage with cutting-edge technologies, ensuring that team members are at the forefront of the data transformation landscape.
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We think this is how you could land Principal Data Architect in Nottingham
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We think you need these skills to ace Principal Data Architect in Nottingham
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at UST, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at UST. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at UST
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
