At a Glance
- Tasks: Deliver AWS-based data solutions and develop AI capabilities in a dynamic environment.
- Company: Join a government client focused on innovative data engineering.
- Benefits: Competitive salary, hybrid work model, and strong potential for contract extension.
- Other info: Opportunity to work on cutting-edge AI initiatives and grow your career.
- Why this job: Make an impact by bridging data engineering and AI in a collaborative setting.
- Qualifications: 4-8+ years in data engineering/BI with AWS experience and problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
Salary: £To be confirmed on application (our client has asked for this not to be advertised).
Location: Swindon or London (Hybrid - once a month max)
Contracting Authority: Government Client
Contract Length: Initial 3 months (strong extension potential)
Clearance: BPSS
Role Split:
- ~50% Business Intelligence / Data Engineering delivery & support
- ~50% New capability development, including data platform and AI initiatives
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
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
Core Technical Requirements:
- 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):
- 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
Currently, this experience does not need to be a core specialism but must be clearly evidenced and practical.
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)
Business Intelligence Engineer (AWS / AI Exposure) – 14793 employer: Comxps Ltd
As a Business Intelligence Engineer with our esteemed government client, you will thrive in a dynamic and collaborative work environment that values innovation and professional growth. Located in either Swindon or London, this role offers the unique opportunity to engage in cutting-edge AI initiatives while contributing to impactful data solutions, all within a supportive culture that encourages continuous learning and development. With strong potential for contract extension and a focus on meaningful projects, this position is ideal for those seeking a rewarding career in the public sector.
StudySmarter Expert Advice🤫
We think this is how you could land Business Intelligence Engineer (AWS / AI Exposure) – 14793
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can land you that interview.
✨Tip Number 2
Prepare for those interviews by brushing up on your AWS and AI knowledge. We recommend creating a cheat sheet of key concepts and examples from your past work to showcase your skills effectively.
✨Tip Number 3
Don’t forget to tailor your pitch! When you get the chance to speak with potential employers, highlight your experience with data engineering and how it relates to their needs. We want to see you shine!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always looking for talented individuals like you to join our team and make an impact.
We think you need these skills to ace Business Intelligence Engineer (AWS / AI Exposure) – 14793
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your AWS and AI exposure, as well as any relevant data engineering projects you've worked on. We want to see how you fit into our world!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about the role and how your background aligns with our needs. Be sure to mention your problem-solving skills and collaborative approach – we love that!
Showcase Your Technical Skills:When detailing your experience, focus on the technical skills listed in the job description, like SQL, Python, and AWS tools. We’re looking for practical examples of how you've used these technologies in your previous roles.
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 don’t miss out on any important updates. Plus, we love seeing applications come in through our platform!
How to prepare for a job interview at Comxps Ltd
✨Know Your AWS Inside Out
Make sure you brush up on your knowledge of the AWS Data Engineering stack, especially Glue, S3, Lambda, Redshift, and Athena. Be ready to discuss how you've used these tools in past projects and how they can be applied to the role.
✨Showcase Your Problem-Solving Skills
Prepare examples that highlight your problem-solving abilities, particularly in complex or regulated environments. Think of specific challenges you've faced and how you tackled them, as this will demonstrate your hands-on engineering mindset.
✨Bridge Data Engineering and AI
Since the role involves AI initiatives, be prepared to discuss your exposure to AI/ML concepts. Share any experiences you've had with cloud-based AI services like AWS Bedrock and how you've collaborated with Data Science teams.
✨Be Proactive and Collaborative
Emphasise your proactive approach and ability to work collaboratively. Prepare to discuss how you've contributed to team projects and supported new capability developments in previous roles, as this aligns well with the job's requirements.
