Business Intelligence Engineer

Job Title: Business Intelligence Engineer (AWS / AI Exposure) Location: Swindon or London (Hybrid – once a month max) Contract: Initial 3 months (strong extension potential) \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Role Overview We’re looking for an experienced Business Intelligence Engineer / AWS Data Engineer to support the development of a modern data platform and contribute to emerging AI-driven initiatives. This role will suit someone with a strong foundation in AWS data engineering and BI, alongside practical exposure to AI/ML concepts or tools. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key Responsibilities • Design, build and optimise data pipelines and data platform components within AWS • Support and enhance Business Intelligence reporting and analytics capabilities • Contribute to the development of a data lake and modern data architecture • Work across both BAU support and new capability development • Collaborate with wider teams on AI-related initiatives and roadmap delivery • Apply best practices around data quality, governance and performance optimisation \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Core Technical Requirements Strong hands-on experience with: • AWS Data Engineering stack (e.g. Glue, S3, Lambda, Redshift, Athena) • SQL (advanced level) • Python (for data processing and pipeline development) • Infrastructure / tooling exposure (e.g. Terraform, APIs, CI/CD beneficial) • Experience working in Business Intelligence / analytics environments \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ AI / ML Exposure (Key Requirement) Candidates must demonstrate some level of 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 / prompt engineering concepts • Exposure to ML pipelines or collaborating with Data Science teams This does not need to be a core specialism but must be clearly evidenced and practical. \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Experience Required • Typically 4–8+ years’ experience in data engineering / BI roles • Proven experience delivering AWS-based data solutions • Background in data warehousing, analytics, or data platform development • Experience working in complex or regulated environments is beneficial \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Desirable • Knowledge of AWS AI services (e.g. Bedrock) • Experience contributing to data lake builds or modern data platforms • Exposure to DataOps / CI-CD practices • Public sector experience (nice to have) Role Split • ~50% Business Intelligence / Data Engineering delivery & support • ~50% New capability development, including data platform and AI initiatives \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Key Attributes • Strong problem solver with a hands-on engineering mindset • Comfortable working in a developing / evolving environment • Able to bridge the gap between data engineering and emerging AI use cases • Proactive and collaborative approach \_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_\_ Summary This is an opportunity to join an organisation investing heavily in its data platform and future AI capabilities, where you’ll play a key role in shaping both current BI delivery and next-generation data solutions.