Principal Data Architect (Principal Data Engineer – Data Architect II)

Company: UST
Apply for the Principal Data Architect (Principal Data Engineer – Data Architect II)
Location: Nottingham
Job Description:

Role Description

Principal Data Architect

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

Skills

  • data architecture
  • data processing
  • aws glue
  • cloud technology

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Posted: July 7th, 2026