Data Engineer (Minerva SA Reg Risking)
Day rate £525
Clearance Required: SC
Duration: 6 months
Telford with 2 days/week in the office
My client is looking for a Senior Data Engineer to join a new Scrum team working on a high-impact initiative within the clients preventative risking (PR) programme. This role will focus on the development and deployment of data ingestion and risking capabilities within the SAS Platform, including Intelligent Data Platform (IDP) components, as part of the Minerva Platform.
This is a unique opportunity to contribute to a mission-critical government data platform that combines 20+ data sources, advanced risk modelling using SAS Viya, and cutting-edge data engineering practices.
Key Responsibilities
Design, develop, and deploy data integration and transformation pipelines using Pentaho, Talend, Denodo, and SAS.
Architect scalable data solutions to support analytics and BI use cases across the SAS platform.
Collaborate with data scientists, analysts, architects, and stakeholders to define technical requirements and deliver high-quality outcomes.
Drive Agile/Scrum methodologies, supporting sprint planning, delivery, and retrospectives.
Implement DevOps best practices for CI/CD pipelines, automated testing, and deployment.
Mentor junior engineers and contribute to a culture of continuous learning and innovation.
Ensure data governance, quality, and security standards are embedded in all solutions.
Troubleshoot and optimise data pipelines, addressing performance bottlenecks and system issues.
Tech Stack \& Skills Required
SAS 9.4, SAS Viya 3.x (including SAS Studio, Visual Analytics, Visual Investigator)
ETL Tools: Pentaho, Talend
Data Virtualisation: Denodo
Version Control \& CI/CD: GIT, Jenkins
DevOps Tools: Docker, Kubernetes (preferred)
Task Management \& Support Tools: Jira, LSF Platform
Strong SQL and data modelling experience
Knowledge of Oracle databases (desirable)
Excellent communication and problem-solving skills
Qualifications \& Experience
Proven experience delivering enterprise data solutions across complex environments.
Strong track record in Agile development and data engineering best practices.
Experience working with multi-disciplinary teams in a secure, high-compliance environment.
Certifications in Agile/Scrum, DevOps, or relevant data technologies (highly desirable).