SC Technical Assurance Engineer CGEMJP00363660

Experis UK; Telford; Hybrid; GBP 87,000 - 114,000; Full time

Job summary

Experis is seeking an experienced Technical Assurance Engineer for a 6-month contract in Telford. The role focuses on assuring discovery outputs for a large data migration and DWIT programme, with AI-assisted analysis and human review to ensure complete, accurate, and traceable legacy data representations.

The successful candidate will work with data engineers, architects and SMEs to define QA standards, oversee governance of artefacts, and validate completeness across the backlog, ensuring

Qualifications

• Defined and implemented technical assurance or QA strategies within large-scale data migration/transformation programmes.
• Strong understanding of data warehousing concepts: ETL/ELT, mappings, lineage, schemas and interfaces.
• Experience assuring documentation against implementation evidence for accuracy and completeness.
• Practical experience using AI-assisted approaches for engineering, analysis or QA.
• Ability to define measurable quality criteria, sampling approaches and acceptance thresholds.
• Experience with legacy ETL/ELT tooling (Informatica, Pentaho, Oracle PL/SQL, COBOL, SAP Data Services) advantageous.

Responsibilities

• Establish quality standards, validation criteria and acceptance thresholds for all documentation artefacts (mappings, transformations, lineage, specifications).
• Implement QA best practices for legacy feeds aligned to project strategy.
• Design and oversee QA processes to verify AI analysis outputs reflect legacy system behaviour, including AI checks and manual reviews.
• Ensure AI-enabled tooling outputs are consistent, accurate and contextually valid.
• Validate completeness and traceability across artefacts and link outputs to source code and logic.
• Identify and manage quality risks, gaps and inconsistencies across backlog with SMEs and team.
• Collaborate with SMEs, data engineers and leads to define assurance approaches for complex transformations and edge cases.
• Oversee governance of artefact repositories and version control practices.
• Lead quality reviews, audits and walkthroughs with stakeholders before handoff to migration teams.

Skills

QA strategy

Data warehousing

ETL/ELT

AI-assisted QA

Quality criteria

Traceability

Cross-team collaboration

Tools

Informatica PowerCenter

Pentaho Data Integration

Oracle PL/SQL

Shell scripting

COBOL

SAP Data Services

Job description

Role Title: Technical Assurance Engineer

Duration: 6 month contract

Location: Telford. Hybrid, twice per month onsite

Rate: up to £544.64 p/d Umbrella inside IR35

Clearance required: Active SC Clearance held with a governing body

Role purpose / summary

Supporting the client's Data Warehousing and Integration Transformation (DWIT) programme, we are supporting the discovery of hundreds of legacy data feeds across diverse technical stacks, with complex interdependencies. Analysing and documenting the legacy solutions, using AI assistance with human and agentic assurance, is the critical first step to enabling migration teams to successfully transform these services into cloud-native solutions.

Assurance of the discovery output is critical to successful completion not just of discovery, but the migration programme as a whole.

Legacy services are formed of various technologies, including SQL, PL/SQL, bash scripts, Informatica Power Centre, Pentaho Data Integration, COBOL, SAP Data Services, and others.

Discovery will be supported by several teams of data engineers, architects, business analysts, and assurance leads, working through a backlog of 1000+ feeds to document all functionality.

This role

Your core responsibility will be to establish whether the discovery output provides a complete, accurate, and traceable representation of the legacy data solution, sufficient for migration teams to rebuild the feed accurately.

Outputs will include design documentation, interface catalogues, schema definitions, business and technical metadata, source-to-target mappings, markdown (or equivalent) code specifications, and structured knowledge captured within custom RAG-backed AI solutions.

With the volume of feeds to transform, the programme's desired pace of delivery, and modern engineering practices, use of AI will be central to the team's ways of working. Since these systems underpin key business processes, assuring that the new systems give equivalent outputs to the existing ones is a core acceptance criteria. Discovery and legacy support teams will also support comparison testing of the new and old systems to validate this.

Working closely with your discovery team, you will:

• Establish quality standards, validation criteria and acceptance thresholds for all documentation artefacts, including mappings, transformations, lineage and specifications
• Implement quality assurance best practices for the legacy feeds in your team's scope, aligned to the overall project strategy
• Design and oversee QA processes to verify that outputs of the AI analysis pipeline accurately reflect legacy system behaviour, including both AI-accelerated checks and manual review approaches
• Assure the use of AI-enabled tooling and prompt engineering outputs, ensuring that generated artefacts are consistent, accurate and contextually valid
• Validate completeness and traceability across artefacts, ensuring that all relevant legacy inputs are accounted for and that outputs can be clearly linked back to source code and logic
• Identify and manage quality risks, gaps and inconsistencies across the backlog, working with legacy service SMEs and your team to address gaps
• Collaborate with SMEs, data engineers and technical leads to define assurance approaches for complex or service-specific transformations and edge cases
• Oversee quality governance of output artefact repositories, ensuring adherence to agreed structures, formats and version control practices
• Lead quality reviews, audits and walkthroughs with stakeholders, ensuring confidence in outputs prior to handoff to the feed migration teams

Skills required

• Proven experience defining and implemented technical assurance or QA strategies within large-scale data migration, modernisation or transformation programmes.
• Strong understanding of data engineering and data warehousing concepts, including ETL/ELT processing, SQL, data mappings, lineage, schema definitions, interfaces, and reconciliation. You will need sufficient technical depth to challenge discovery findings and identify where documented behaviour is wrong or incomplete.
• Experience assuring technical documentation or specs against implementation evidence, with the ability to assess accuracy and completeness.
• Practical experience using AI-assisted approaches for engineering, analysis or QA, with an understanding of the limitations of such approaches.
• Experience defining measurable quality criteria, sampling approaches, and acceptance thresholds.
• Experience with legacy ETL/ELT tooling such as Informatica PowerCenter, Pentaho Data Integration, Oracle PL/SQL, shell scripting, COBOL, or SAP Data Services would be advantageous.

All profiles will be reviewed against the required skills and experience. Due to the high number of applications we will only be able to respond to successful applicants in the first instance. We thank you for your interest and the time taken to apply!

If you receive suspicious outreach claiming to be from us, please contact us via the ManpowerGroup website.