At a Glance
- Tasks: Design and optimise data pipelines while contributing to AI-driven projects.
- Company: Dynamic tech company focused on innovative data solutions.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Inclusive workplace with strong support for diverse backgrounds.
- Why this job: Join a cutting-edge team at the forefront of data engineering and AI.
- Qualifications: Experience in AWS data stack and AI/ML exposure required.
The predicted salary is between 55000 - 65000 £ per year.
Location: Swindon or London (Hybrid - approx. once per month onsite)
Contract: Initial 3 months (strong extension potential)
IR35: Inside IR35
Clearance: BPSS required
Overview
We're 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. This role offers the opportunity to work at the intersection of data engineering, business intelligence, and AI, helping to shape both current analytics capabilities and future data solutions.
Key Responsibilities
- Design, build, and optimise data pipelines and platform components within AWS
- Support and enhance Business Intelligence reporting and analytics
- Contribute to the development of a modern data lake and data architecture
- Deliver across both BAU support and new capability development
- Collaborate with cross-functional teams on AI initiatives and roadmap delivery
- Apply best practices for data quality, governance, and performance optimisation
Core Technical Skills
- Strong hands-on experience with AWS data stack (Glue, S3, Lambda, Redshift, Athena)
- Advanced SQL
- Python for data processing and pipeline development
- Exposure to tooling such as Terraform, APIs, or CI/CD pipelines (desirable)
- Experience working in Business Intelligence / analytics environments
- AI / ML Exposure (Essential)
Candidates must demonstrate 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 generative AI concepts, including prompt engineering
- Exposure to ML pipelines or collaboration with Data Science teams (This does not need to be a core specialism but must be clearly evidenced.)
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 Experience
- Knowledge of AWS AI services (e.g. Bedrock)
- Experience contributing to data lake or modern data platforms
- Exposure to DataOps / CI-CD practices
- Experience in the public sector (nice to have)
Role Split
- ~50% BI / Data Engineering delivery and 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 fast-paced, evolving environment
- Ability to bridge data engineering and AI use cases
- Proactive, collaborative, and delivery-focused
Additional Information
This organisation is part of the Disability Confident scheme and Armed Forces Covenant. Candidates eligible for the Guaranteed Interview Scheme should highlight this in their application.
Reasonable Adjustments: Respect and equality are core values to us. We are proud of the diverse and inclusive community we have built, and we welcome applications from people of all backgrounds and perspectives. Our success is driven by our people, united by the spirit of partnership to deliver the best resourcing solutions for our clients.
If you need any help or adjustments during the recruitment process for any reason, please let us know when you apply or talk to the recruiters directly so we can support you.
Business Intelligence Engineer (AWS / AI Exposure) employer: Sanderson Government and Defence
Join a forward-thinking organisation that values innovation and inclusivity, offering a dynamic work culture where collaboration thrives. As a Business Intelligence Engineer in Swindon or London, you'll have the chance to work on cutting-edge AI initiatives while enjoying flexible hybrid working arrangements and opportunities for professional growth. With a commitment to diversity and support for all employees, this company stands out as an excellent employer for those seeking meaningful and rewarding careers.
Contact Details:
Sanderson Government and Defence Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Business Intelligence Engineer (AWS / AI Exposure)
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in the game. We can’t stress enough how valuable personal connections can be when it comes to landing that Business Intelligence Engineer role.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your hands-on experience with AWS tools and any AI projects you've worked on. We want to see your passion and expertise shine through, so be ready to discuss your past successes and how they relate to the job.
✨Tailor Your Approach
Every company is different, so make sure you tailor your conversations to fit their needs. Research the company’s current data initiatives and think about how your skills can help them achieve their goals. We’re all about making those connections, so show them you’ve done your homework!
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for talented individuals like you to join our team and contribute to exciting projects in the BI and AI space.
We think you need these skills to ace Business Intelligence Engineer (AWS / AI Exposure)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your AWS data stack experience and any AI exposure you've had. We want to see how you can contribute to our data platform!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about this role and how your background in BI and data engineering makes you a perfect fit. Let us know what excites you about working with AI initiatives.
Showcase Your Projects:If you've worked on relevant projects, don’t hold back! Include specific examples of how you've designed or optimised data pipelines, especially using AWS tools. We love seeing practical applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Sanderson Government and Defence
✨Know Your AWS Inside Out
Make sure you brush up on your knowledge of the AWS data stack, especially Glue, S3, Lambda, Redshift, and Athena. Be ready to discuss how you've used these tools in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your AI Exposure
Since this role requires practical exposure to AI/ML, prepare examples of how you've worked with cloud-based AI services or contributed to AI-enabled data products. Highlight your understanding of generative AI concepts and any collaboration with Data Science teams.
✨Demonstrate Problem-Solving Skills
Be prepared to tackle some technical questions or case studies during the interview. Think about how you can showcase your problem-solving abilities, particularly in fast-paced environments. Use specific examples from your experience to illustrate your approach.
✨Collaborate and Communicate
This role involves working with cross-functional teams, so be ready to discuss your collaborative experiences. Share how you've effectively communicated with different stakeholders and contributed to team success, especially in delivering new capabilities or supporting existing ones.
