Coltech
Lead Data Architect
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Lead Data Architect – AI, Data & Cloud Platforms
Location: Manchester / Leeds / Halifax (Hybrid – 2 Days Per Week Onsite)
Contract Type: Long-Term Contract (Inside IR35)
Department: Enterprise Data & Analytics
Overview
We are seeking an experienced Lead Data Architect to drive the design and evolution of enterprise-scale data platforms supporting advanced analytics, artificial intelligence, and cloud transformation initiatives.
This role sits at the intersection of Data Architecture, Cloud Engineering, and AI Enablement, responsible for defining scalable data foundations that support both traditional analytics and emerging Generative AI use cases. You will lead the architecture of modern data platforms, ensuring data is secure, governed, accessible, and capable of supporting large-scale AI, machine learning, and real-time decisioning workloads.
Working closely with senior stakeholders, engineering teams, data scientists, and platform teams, you will define target-state architectures, establish best practices, and provide technical leadership across strategic transformation programmes.
Key Responsibilities
Enterprise Data Architecture
- Define and maintain enterprise-wide data architecture strategies, principles, standards, and roadmaps.
- Design scalable data ecosystems supporting analytical, operational, and AI-driven workloads.
- Lead architecture reviews, governance forums, and design authority activities.
- Drive adoption of modern data architecture patterns including Data Lake, Lakehouse, Data Mesh, and Data Fabric.
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AI & Data Platform Enablement
- Design enterprise architectures supporting Generative AI, Retrieval-Augmented Generation (RAG), and Machine Learning initiatives.
- Define frameworks for vector databases, semantic search, and AI-ready data pipelines.
- Establish scalable and secure data foundations for AI and advanced analytics workloads.
- Collaborate closely with Data Science, Engineering, and Platform teams to support AI adoption at scale.
Cloud & Platform Architecture
- Lead architecture across cloud-native data platforms within AWS, Azure, or GCP environments.
- Define patterns for data ingestion, storage, transformation, orchestration, and real-time processing.
- Support cloud migration, platform modernisation, and enterprise data transformation initiatives.
- Ensure solutions align with enterprise security, resilience, and operational requirements.
Data Governance & Security
- Define and implement data governance frameworks covering lineage, metadata, data quality, and compliance.
- Design controls for data privacy, masking, anonymisation, and protection of sensitive information.
- Support enterprise data cataloguing and governance tooling.
- Ensure alignment with regulatory, security, and risk management requirements.
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Leadership & Stakeholder Management
- Partner with senior business and technology stakeholders to translate strategic objectives into data architecture roadmaps.
- Provide architectural leadership across multiple workstreams and delivery teams.
- Influence technology strategy, standards, and investment decisions.
- Act as a trusted advisor for enterprise data, AI, and cloud transformation programmes.
Required Experience
- 8+ years of experience within Data Architecture, Enterprise Architecture, Data Engineering, or Cloud Architecture environments.
- Proven experience designing and delivering large-scale enterprise data platforms.
- Strong understanding of AI, Machine Learning, and Generative AI data requirements.
- Experience with modern data architecture approaches including Data Lakes, Lakehouses, Data Mesh, and Data Fabric.
- Deep expertise across at least one major cloud platform:
- AWS
- Bedrock
- SageMaker
- Glue
- Redshift
- S3
- Azure
- Azure OpenAI
- Azure Machine Learning
- Synapse Analytics
- Data Factory
- GCP
- Vertex AI
- BigQuery
- Dataflow
- AWS
- Strong data modelling expertise across relational, NoSQL, analytical, and vector-based data platforms.
- Hands-on experience with technologies such as Spark, Kafka, Flink, Airflow, or equivalent.
- Strong Python and SQL skills.
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