Job Description
Business Intelligence / Data Engineer (AWS / AI Exposure)
Swindon or London - Hybrid (Once per month onsite)
£530 PD – Inside IR 35 – 3 months (likely extension) – Start ASAP.
Our trusted client, that operates within the public sector and helps millions of people in the UK with funding investment is seeking an experienced Business Intelligence Engineer / AWS Data Engineer to support the development of a modern data platform and contribute to emerging AI-driven initiatives (ML) paying up to £530PD Inside IR 35, one day onsite per month in either Swindon or London.
This is an exciting opportunity to join an organisation investing heavily in its data platform and future AI capabilities, with the successful candidate playing a key role in shaping both current Business Intelligence delivery and next-generation data solutions.
This role will suit someone with a strong foundation in AWS data engineering and Business Intelligence, alongside practical exposure to AI/ML concepts or tools.
Role and Responsibilities:
- Data Engineering: Design, build and optimise data pipelines and data platform components within AWS.
- Business Intelligence: Support and enhance Business Intelligence reporting and analytics capabilities.
- Data Architecture: Contribute to the development of a data lake and modern data architecture.
- Platform Development: Work across both BAU support and new capability development, with approximately 50% of the role focused on Business Intelligence and Data Engineering delivery and 50% focused on data platform and AI initiatives.
- AI Initiatives: Collaborate with wider teams on AI-related initiatives and roadmap delivery.
- Data Governance: Apply best practices around data quality, governance and performance optimisation.
- Stakeholder Collaboration: Work closely with technical and business teams to deliver high-quality data solutions and support organisational objectives.
- Continuous Improvement: Identify opportunities to improve processes, automation, tooling, and platform performance.
Skills and Experience:
- 4–8+ years' experience in Data Engineering, Business Intelligence or related roles
Strong hands-on experience with:
- AWS Data-based solutions and engineering stack (e.g. Glue, S3, Lambda, Redshift, Athena)
- SQL (advanced level)
- Python (for data processing and pipeline development)
- Infrastructure and tooling exposure (e.g. Terraform, APIs, CI/CD)
AI / ML Exposure (Key Requirement):
Practical exposure to AI/ML, such as:
- Working with cloud-based AI services (e.g. AWS Bedrock or similar)
- Supporting AI-enabled data products or workflows
- Understanding of generative AI and prompt engineering concepts
- Exposure to ML pipelines or collaboration with Data Science teams
Key Attributes
- Strong problem-solving skills with a hands-on engineering mindset
- Comfortable working within a developing and evolving environment
- Ability to bridge the gap between data engineering and emerging AI use cases
- Proactive, collaborative and delivery-focused approach
- Strong communication and stakeholder management skills
Desirable
- Experience contributing to data lake builds or modern data platforms
- Experience working in complex or regulated environments is beneficial
- Exposure to Data Ops and CI/CD practices
- Public sector experience
Please note: BPSS clearance is essential