SC Cleared Technical/Data/Lead Architect

DWIT Technical Architect
Clearance Required: Current SC (HMRC SC would be an advantage) Candidates will not be able to start until their SC clearance has been transferred/shared with HMRC
Duration: 6 months
Location: Telford - 2 days onsite per week
IR35 Status: Capgemini Mandated PAYE only
Job Description:

Role Purpose

The DWIT Data Architect is responsible for producing the detailed analysis, documentation and architecture artefacts needed to support the transformation of existing data feeds to AWS and the planned decommissioning of Legacy services.

The role works under the direction of Lead Architects, turning complex Legacy information into clear, structured and delivery-ready outputs. It is a hands-on role focused on feed discovery, dependency analysis, documentation quality, option development and practical support to migration and decommissioning planning.

Context

DWIT is undertaking a significant transformation of existing data feeds and Legacy services onto AWS. The work requires disciplined discovery, consistent documentation, clear architectural judgement and practical decommissioning plans that can be executed safely across a complex client and supplier landscape.

The Data Architect will work closely with Lead Architects, engineers, delivery teams, operations teams and client stakeholders to understand existing feeds, capture relevant detail, identify gaps and help shape the information needed for AWS transformation and Legacy service retirement.

Core Accountabilities

The Data Architect is accountable for producing accurate, clear and evidence-based architecture outputs within assigned DWIT workstreams, working to the standards and direction set by the Lead Architects.

Accountabilities include:

Discovering, analysing and documenting existing data feeds, interfaces, dependencies, service ownership, operational constraints and business usage.

Applying agreed documentation standards, templates and quality expectations so feed analysis is consistent, traceable and usable by engineering, delivery, operations and governance teams.

Supporting the definition of target-state AWS transformation approaches for existing feeds, including data movement, processing, integration, security, resilience, observability and support considerations.

Contributing to decommissioning strategies for Legacy services by documenting dependencies, migration sequencing, risks, parallel running needs, cutover considerations and retirement evidence.

Using AI-enabled tools to accelerate feed discovery, documentation, code and metadata analysis, dependency identification and production of draft architecture artefacts, with appropriate review by Lead Architects.

Capturing assumptions, risks, issues and decisions clearly, ensuring they are visible to Lead Architects and supported by evidence where possible.

Working with Lead Architects, delivery leads, engineers, operations teams, client stakeholders and third parties to gather information, validate findings and support realistic transformation and decommissioning plans.

Preparing architecture artefacts for review, including feed documentation, dependency maps, option summaries, impact assessments, risk logs and design inputs.

Communicating findings clearly and escalating gaps, conflicts, risks or incomplete information that could affect delivery confidence.

Expected Outcomes

The role is expected to produce clear, usable outputs that support Lead Architects, engineering teams and delivery governance across the DWIT transformation.

Expected outcomes include:

Accurate and complete documentation of assigned feeds, interfaces, dependencies, service owners, schedules, consumers and operational constraints.

Clear analysis packs that support AWS transformation options, including current-state findings, gaps, risks, assumptions and candidate target patterns.

Decommissioning inputs that identify dependencies, sequencing considerations, controls, evidence requirements and conditions for retiring Legacy services.

Architecture artefacts that are structured, evidence-based and ready for review by Lead Architects and programme governance.

Practical use of AI-enabled approaches to improve the speed and consistency of discovery and documentation, with outputs checked and refined before use.

Skills and Experience

The role requires a hands-on data architect with experience analysing complex Legacy environments, documenting data flows and supporting cloud transformation or migration activity.

Required experience includes:

Producing architecture documentation and analysis outputs to agreed standards, with enough clarity and evidence to support review, decision-making and delivery planning.

Documenting and analysing complex Legacy data feeds, interfaces, schedules, source systems, consumers, business rules, service dependencies and operational constraints.

Supporting migration and transformation approaches for AWS-based data services, including data pipelines, storage, processing, integration, security, monitoring and support considerations.

Contributing to decommissioning planning for Legacy platforms and services, including dependency analysis, migration sequencing, risk identification and evidence-based retirement decisions.

Working within architecture governance in a large, multi-supplier environment, including preparing artefacts for design assurance, decision control, risk management and alignment to enterprise standards.

Using AI and automation tools to improve the speed and quality of discovery, documentation, analysis and architecture production, with appropriate checking and evidence.

Experience across on-premise, cloud or hybrid environments, with understanding of the practical challenges involved in transforming Legacy services to AWS.

Clear communication and facilitation skills, especially when gathering information, validating findings and explaining Legacy dependencies or transformation impacts.

Ways of Working

The Data Architect is expected to operate as a hands-on contributor within the architecture team, working to the direction of Lead Architects while taking ownership for the quality and completeness of assigned outputs.

Expected ways of working include:

Working to priorities, standards, expected outputs, review points and delivery milestones set by the Lead Architects.

Working collaboratively with architects, engineers, operations, delivery teams, client stakeholders and third parties to gather information, validate findings and resolve gaps.

Identifying incomplete analysis, weak assumptions, unclear decisions or documentation gaps and raising them early for resolution.

Communicating findings in plain English, with clear evidence, assumptions, risks and recommended next steps.

Maintaining pace and quality where documentation gaps, Legacy complexity or changing priorities create ambiguity.

Use of AI and Automation

The role should use AI and automation to improve the speed, consistency and quality of discovery, documentation and analysis. AI should be used as an accelerator, with outputs checked before they are used to support architecture decisions or delivery artefacts.

Expected uses include:

Accelerating analysis of Legacy code, configuration, metadata, schedules, schemas, interface definitions and existing documentation.

Supporting feed documentation, dependency mapping, option development, risk identification and production of architecture artefacts.

Reusing agreed prompts, templates, patterns and review checklists provided by Lead Architects or the wider DWIT architecture team.

Checking, refining and evidencing AI-generated outputs before they are shared for review or used in architecture artefacts.