At a Glance
- Tasks: Design and optimise data architectures while delivering end-to-end data solutions.
- Company: Join a forward-thinking company embracing cloud technology and AI.
- Benefits: Remote work flexibility, competitive salary, and opportunities for professional growth.
- Other info: Work in a dynamic environment with occasional meet-ups in London or Swindon.
- Why this job: Be at the forefront of data innovation and make a real impact in the tech world.
- Qualifications: Experience with AWS Data Stack, SQL, Python, and cloud-based AI services.
The predicted salary is between 60000 - 80000 £ per year.
We are hiring for a position that requires hands-on experience in Data Engineering, Data Warehousing, and Business Intelligence (BI) roles, with a proven track record of delivering end-to-end data solutions.
Advanced proficiency in the AWS Data Stack (Glue, S3, Lambda, Redshift, Athena) alongside expert-level SQL and Python for complex pipeline development and data processing is essential.
Practical, demonstrable experience with cloud-based AI services (such as AWS Bedrock), prompt engineering, generative AI workflows, or collaborating on Machine Learning pipelines is required.
The role involves designing, building, and optimizing modern data architectures and data lakes, while seamlessly balancing new capability development with BAU reporting and analytics support.
Practical exposure to Infrastructure as Code (IaC) tools like Terraform, API integrations, and CI/CD pipelines to support a modern DataOps framework is necessary.
Public Sector experience is highly desirable.
- AWS Data Ecosystem
- AWS Glue
- S3
- Redshift
- Lambda
- Athena
- Python
- Cloud AI Services
- AWS Bedrock
- LLMs
- Data Science
- DataOps
Business Intelligence Engineer (AWS Stack /AI Exposure / Data Science / DataOps) in London employer: GIOS Technology
Join a forward-thinking company that values innovation and collaboration, offering a dynamic work culture where your contributions as a Business Intelligence Engineer will directly impact our data-driven decision-making. With flexible remote working options and occasional meet-ups in vibrant locations like Swindon or London, you will enjoy a supportive environment that fosters professional growth through continuous learning and exposure to cutting-edge technologies in the AWS ecosystem. Our commitment to employee development and a strong focus on work-life balance make us an exceptional employer for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Business Intelligence Engineer (AWS Stack /AI Exposure / Data Science / DataOps) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the 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 help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving AWS and data engineering. We recommend using platforms like GitHub to share your code and demonstrate your expertise in Python and SQL.
✨Tip Number 3
Prepare for interviews by brushing up on common BI and DataOps questions. We suggest doing mock interviews with friends or using online resources to get comfortable discussing your experience with AWS tools and AI services.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Business Intelligence Engineer (AWS Stack /AI Exposure / Data Science / DataOps) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your hands-on experience with AWS Data Stack and any relevant projects you've worked on. We want to see how you can bring value to our team!
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 in Data Engineering and Business Intelligence makes you a perfect fit. Don’t forget to mention any public sector experience if you have it!
Showcase Your Technical Skills:Be specific about your technical abilities, especially with tools like Glue, Redshift, and Python. If you've worked with AI services or DataOps frameworks, make sure to include those details. We love seeing practical examples of your work!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at GIOS Technology
✨Know Your AWS Stack Inside Out
Make sure you brush up on your knowledge of the AWS Data Stack, especially Glue, S3, Redshift, Lambda, 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.
✨Show Off Your Data Engineering Skills
Prepare to talk about your hands-on experience in Data Engineering and Business Intelligence. Have specific examples ready that demonstrate your ability to deliver end-to-end data solutions, and don’t forget to highlight your SQL and Python skills for pipeline development.
✨Get Familiar with AI Services
Since the role involves cloud-based AI services, make sure you understand how AWS Bedrock and generative AI workflows work. Be prepared to discuss any relevant experience you have with Machine Learning pipelines and how you've integrated AI into your data solutions.
✨Emphasise Your DataOps Knowledge
Talk about your practical exposure to Infrastructure as Code (IaC) tools like Terraform and your experience with CI/CD pipelines. Highlight how you've supported a modern DataOps framework in previous roles, as this will show your ability to balance new capability development with ongoing reporting and analytics.
