Principal Data Platform Architect

About the role 

The Principal Data Platform Architect acts as the senior technical authority for the organisation’s data platform technology landscape, accountable for defining, governing, and evolving the platforms that underpin Data Foundations, Data Products, analytics, and AI use cases at enterprise scale. 

This role owns the strategic and target‑state architecture of the data platform, including cloud data services, processing engines, integration and streaming technologies, and platform‑level capabilities such as security, resilience, scalability, and performance. Working closely with data engineering, data architecture, security, and platform operations teams, the Principal Data Platform Architect ensures that all Data & AI solutions are built on a consistent, secure, and reusable platform architecture aligned to agreed enterprise standards and principles. 

Operating at Principal level, the role balances deep technical leadership with architectural governance and assurance. It is responsible for evaluating new data technologies, defining reference architectures and patterns, and guiding complex platform‑level decisions and trade‑offs across the organisation. The role plays a critical part in ensuring that platform evolution supports long‑term business value, cost efficiency, and operational sustainability, rather than short‑term project optimisation. 

The Principal Data Platform Architect partners closely with Enterprise, Solution and Data Architects, ensuring that platform decisions enable domain‑aligned Data Foundations and Value Pool delivery, without driving fragmentation or unnecessary divergence. While Solution Architects focus on end‑to‑end solution design for individual initiatives, this role remains focused on the platform as a product, ensuring coherence, scalability, and reuse across all delivery streams. 

The role sits within the Data Architecture and Engineering team in the Data and AI Office. 

Key responsibilities 

Data platform strategy & target architecture 

• Define, optimise, and govern the specialised technology landscape for the organisation’s Data Platforms.  

• Establish and maintain target‑state platform architectures that support scalable analytics, AI, and data product delivery.  

Architecture standards, principles & patterns 

• Define and govern data platform architecture standards, principles, reference architectures, and design patterns.  

• Ensure consistent adoption of approved platform technologies and patterns across domains and Value Pools.  

• Act as a custodian of platform consistency, preventing fragmentation and uncontrolled divergence. 

Technology evaluation & platform evolution 

• Evaluate new and emerging data technologies, balancing standardisation, innovation, cost, and risk.  

• Define transition paths from current‑state to future‑state platforms, articulating clear architectural options and trade‑offs.  

• Contribute to technology investment decisions and shaping long‑term platform roadmaps. 

Architectural governance & assurance 

• Provide architectural governance and assurance for data platform designs across major initiatives.  

• Ensure that platform designs are secure, performant, resilient, and scalable before being adopted by delivery teams.  

• Support technology decisions from a position of informed technical authority.  

Cross‑functional collaboration 

• Partner closely with data engineering, platform engineering, security, and operations teams to ensure platform architectures are practical and operable.  

• Work with Enterprise,  Solution and Data Architects to ensure platform capabilities effectively support end‑to‑end solution delivery without owning solution design.  

Security, governance & compliance by design 

• Embed data security, privacy, governance, and regulatory requirements into data platform architectures by design.  

• Ensure platform technologies support appropriate data classification, access controls, and auditability. 

Thought leadership & capability uplift 

• Provide thought leadership in data platform technologies, analytics, data science, AI, and GenAI.  

• Promote strong architectural thinking aligned to enterprise principles rather than project‑specific optimisation.  

Qualifications and skills 

Essential 

• Proven experience in a Data Platform Architect or equivalent senior technical architecture role within a large, complex enterprise environment.  

• Demonstrated track record designing and governing enterprise‑scale data platforms supporting analytics, data products, and AI use cases.  

• Strong hands‑on experience with cloud‑based data platforms (Azure preferred or equivalent), including data lakes, analytics platforms, and integration services.  

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or equivalent practical experience 

• Data Platform Architecture: 

• Deep expertise in data platform architecture, spanning ingestion, transformation, storage, processing, analytics, and integration layers. 

• Strong understanding of cloud data foundations, including lake, lakehouse, or warehouse style patterns. 

• Experience designing platforms that are scalable, performant, resilient, and cost efficient. 

• Architecture Standards & Governance: 

• Proven ability to define, govern, and enforce platform architecture standards, principles, reference architectures, and design patterns. 

• Experience providing architectural assurance across initiatives, ensuring platform designs align to agreed enterprise standards. 

• Ability to prevent platform fragmentation by driving consistent technology adoption across domains and Value Pools. 

• Security, Governance & Compliance: 

• Strong knowledge of data security, privacy, governance, and regulatory requirements, and how to embed these into platform architecture by design. 

• Experience designing platforms that support data classification, access controls, lineage, and auditability. 

• Collaboration & Influence 

• Experience working closely with data engineering, platform engineering, security, and operations teams to ensure architectures are practical and operable. 

• Strong stakeholder management skills, with the ability to articulate architectural trade‑offs, risks, and decisions clearly. 

• Ability to collaborate effectively with Enterprise and Solution Architects without owning end‑to‑end solution design. 

Preferred 

Advanced Platform & Technology Experience 

• Experience with streaming and event‑driven data architectures. 

• Familiarity with modern analytics and AI platforms (e.g. Databricks, Spark‑based platforms, streaming services). 

• Exposure to domain‑aligned or federated data architecture models (e.g. data mesh–influenced approaches). 

Platform Evolution & Transformation 

• Experience contributing to enterprise data platform modernisation or transformation programmes. 

• Ability to define and communicate transition roadmaps from current‑state to future‑state platform architectures. 

• Experience supporting technology evaluation and investment decisions at enterprise level. 

Ways of Working & Leadership 

• Experience operating in Agile and DevOps‑aligned environments, supporting delivery from design through to industrialisation. 

• Experience mentoring or coaching other architects and senior engineers, raising overall architectural maturity. 

• Strong documentation skills for reference architectures, standards, and guidance artefacts. 

Certifications & Industry Context 

• Relevant cloud or architecture certifications (e.g. Azure, TOGAF‑aligned, or equivalent). 

• Experience working in highly regulated or strongly governed industries. 

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