Data Platform Architect

Data & AI Platform Architect (Contract)

Contract Length: 6 months Working Model: Hybrid Overview

We are looking for a highly skilled Data & AI Platform Architect with deep experience in AWS and Azure to lead the design and delivery of modern cloud-native data, analytics and AI platforms. You will architect scalable, secure and sustainable solutions across the entire data value chain-from ingestion and engineering to analytics, MLOps and enterprise-grade Generative AI.

This role suits someone who combines strong architectural leadership with hands-on delivery awareness, advising clients, shaping technical direction and guiding small teams or workstreams. Key Responsibilities

• Architect and design modern AWS and Azure data, analytics and AI platforms, covering both batch and Real Time processing patterns.
• Define and embed robust data management practices across the end-to-end data life cycle: governance, quality, lineage, metadata, access control and security.
• Integrate Machine Learning, Generative AI and Large Language Models into enterprise platforms, leveraging native cloud services (eg Azure OpenAI, Amazon Bedrock, SageMaker, Azure ML).
• Engage with stakeholders to translate business needs into clear, actionable architectures and delivery roadmaps.
• Provide architectural oversight and technical leadership for small delivery teams or workstreams.
• Ensure best-practice use of cloud-native tooling, including serverless, containerisation, event-driven design and scalable storage/compute patterns.
• Support CI/CD, DevOps and infrastructure-as-code practices across AWS and Azure environments (eg Terraform, Bicep, CloudFormation).
• Produce high-quality architectural documentation, HLDs, solution blueprints and technical recommendations.
• Navigate the needs of public sector or regulated environments where required (desirable).

Required Experience & Skills

• 5+ years' experience in data, analytics and AI solution architecture and delivery.
• Strong, practical architectural expertise in AWS and Azure, including services such as:

• AWS: S3, Glue, Lambda, Redshift, MSK/Kinesis, Step Functions, EMR, SageMaker, Bedrock
• Azure: Data Lake, Data Factory, Synapse, Databricks, Event Hub, Functions, Azure ML, Azure OpenAI

• Solid grounding in data engineering and platform-oriented design across batch and streaming workloads.
• Strong understanding of data management, governance and life cycle principles.
• Good working knowledge of CI/CD pipelines, DevOps toolchains and IaC.
• Ability to clearly explain Machine Learning, AI and Data Mining concepts to technical and non-technical audiences.
• Demonstrated experience leading small implementation teams or technical workstreams.
• Excellent communication, client-facing and stakeholder engagement skills.

Desirable Experience

• Previous work in public sector or regulated industries, such as government or healthcare.
• Understanding of compliance frameworks and security requirements in regulated data environments.
• Familiarity with vector databases, RAG patterns, enterprise MLOps/LLMOps and AI platform governance.

Engagement Details

• Contract: 6 months
• Working Model: Hybrid

• 5+ years' experience in data, analytics and AI solution architecture and delivery.
• Strong, practical architectural expertise in AWS and Azure, including services such as:

• AWS: S3, Glue, Lambda, Redshift, MSK/Kinesis, Step Functions, EMR, SageMaker, Bedrock
• Azure: Data Lake, Data Factory, Synapse, Databricks, Event Hub, Functions, Azure ML, Azure OpenAI

• Solid grounding in data engineering and platform-oriented design across batch and streaming workloads.
• Strong understanding of data management, governance and life cycle principles.
• Good working knowledge of CI/CD pipelines, DevOps toolchains and IaC.
• Ability to clearly explain Machine Learning, AI and Data Mining concepts to technical and non-technical audiences.
• Demonstrated experience leading small implementation teams or technical workstreams.
• Excellent communication, client-facing and stakeholder engagement skills.

Desirable Experience

• Previous work in public sector or regulated industries, such as government or healthcare.
• Understanding of compliance frameworks and security requirements in regulated data environments.
• Familiarity with vector databases, RAG patterns, enterprise MLOps/LLMOps and AI platform governance.