At a Glance
- Tasks: Design and optimise AWS data pipelines while enhancing reporting and analytics capabilities.
- Company: Join a forward-thinking company driving AI and data innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with a mix of hands-on engineering and innovative project development.
- Why this job: Be at the forefront of AI-driven data solutions and make a real impact.
- Qualifications: Degree in Computing or related field; experience in BI and AWS required.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking an experienced Business Intelligence Engineer with strong AWS Data Engineering capabilities to support the development of a modern data platform while contributing to emerging AI-driven initiatives. This role is ideal for a hands-on engineer who combines Business Intelligence expertise with AWS data engineering experience and has practical exposure to AI/ML technologies, tools, or initiatives. You will play a key role in enhancing reporting and analytics capabilities, supporting existing data services, and helping shape future data and AI solutions.
Key Responsibilities
- Design, develop, maintain, and optimise AWS-based data pipelines and platform components.
- Develop and support Power BI reports, dashboards, and analytical solutions across multiple business functions.
- Build and maintain robust data models and semantic layers within Power BI.
- Contribute to the development and enhancement of a modern data lake and data platform architecture.
- Support both BAU activities and the delivery of new data and analytics capabilities.
- Collaborate with stakeholders to gather requirements, define user stories, and translate business needs into technical solutions.
- Work closely with technical and business teams to support AI-related initiatives and roadmap delivery.
- Ensure best practices are followed for data quality, governance, security, and performance optimisation.
- Manage Power BI administration activities including access management, role-based security, subscriptions, and gateway configuration.
- Support migration of reporting and data workloads from legacy platforms into modern AWS and Power BI environments.
- Maintain code repositories and contribute to CI/CD and DataOps practices where applicable.
Core Technical Requirements
- Strong hands-on experience with Power BI report and dashboard development.
- Power BI administration, including security, access management, gateways, and subscriptions.
- Advanced SQL development and optimisation.
- AWS services including Athena, S3, Lambda, Glue, Redshift, EC2, and RDS.
- PostgreSQL, Postgres RDS, MySQL, and AWS Athena.
- Data modelling and semantic layer design.
- DAX query language.
- Python for data processing and pipeline development.
- GitHub and source code management.
- Agile delivery environments.
AI / ML Exposure (Essential)
You must demonstrate practical exposure to one or more of the following:
- Working with cloud-based AI services such as AWS Bedrock or similar platforms.
- Supporting AI-enabled products, workflows, or data solutions.
- Exposure to Generative AI technologies and prompt engineering concepts.
- Experience working alongside Data Science teams or supporting ML pipelines.
- Understanding of how AI capabilities can be integrated into data platforms and analytics solutions.
Please note that AI/ML does not need to be your primary specialism; however, practical exposure must be clearly demonstrated.
Experience Required
- Typically 4–8+ years of experience in Business Intelligence, Data Engineering, Analytics Engineering, or related disciplines.
- Proven track record delivering AWS-based data and analytics solutions.
- Strong experience developing Power BI reporting solutions in enterprise environments.
- Experience working with data warehouses, analytics platforms, and modern data architectures.
- Experience supporting and enhancing production reporting environments.
- Ability to engage effectively with technical and non-technical stakeholders.
Desirable Skills
- AWS Bedrock or other cloud AI services.
- Data lake implementation experience.
- Infrastructure as Code (Terraform).
- API integration experience.
- CI/CD and DataOps practices.
- Experience migrating reporting platforms and legacy data solutions.
- Experience working within complex, regulated, or public sector environments.
Role Split
- Approximately 50% Business Intelligence and Data Engineering delivery/support.
- Approximately 50% New capability development including data platform enhancement and AI initiatives.
Key Attributes
- Strong problem-solving and analytical mindset.
- Hands-on engineering approach with attention to detail.
- Comfortable working within evolving and fast-paced environments.
- Ability to bridge the gap between data engineering, analytics, and emerging AI use cases.
- Proactive, collaborative, and delivery-focused.
- Excellent communication and stakeholder engagement skills.
- Able to work independently while contributing effectively within cross-functional teams.
Qualifications Essential
Degree in Computing, Engineering, Data Science, Mathematics, or another numerate discipline.
Business Intelligence Engineer employer: ALOIS UK
Join a forward-thinking company that values innovation and collaboration, where as a Business Intelligence Engineer, you will have the opportunity to work with cutting-edge AWS technologies and contribute to exciting AI-driven projects. Our supportive work culture fosters professional growth through continuous learning and development, while our commitment to data quality and governance ensures you can make a meaningful impact in your role. Located in a vibrant area, we offer a dynamic environment that encourages creativity and teamwork, making it an excellent place for those looking to advance their careers in data and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Business Intelligence Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Power BI reports, AWS projects, and any AI/ML initiatives you've been part of. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to AWS, SQL, and data modelling. Practice explaining your past projects and how they relate to the role you're applying for.
✨Tip Number 4
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 love seeing candidates who are proactive about their job search.
We think you need these skills to ace Business Intelligence Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Business Intelligence Engineer role. Highlight your AWS Data Engineering skills and any experience with AI/ML technologies. We want to see how your background aligns with what we're looking for!
Showcase Your Projects:Include specific projects where you've developed Power BI reports or built data pipelines on AWS. We love seeing real examples of your work, so don’t hold back on the details that demonstrate your hands-on experience.
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 skills can contribute to our team. We appreciate a personal touch that shows you’ve done your homework on us.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining the StudySmarter family!
How to prepare for a job interview at ALOIS UK
✨Know Your Tech Inside Out
Make sure you brush up on your AWS services, especially those mentioned in the job description like S3, Lambda, and Redshift. Be ready to discuss how you've used these tools in past projects, as well as your experience with Power BI and SQL.
✨Showcase Your AI/ML Exposure
Since the role involves AI-driven initiatives, be prepared to talk about any hands-on experience you have with AI/ML technologies. Whether it's working with AWS Bedrock or supporting ML pipelines, make sure you can clearly demonstrate your practical exposure.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems or scenarios related to data engineering and analytics. Think of examples from your previous work where you had to gather requirements, define user stories, or enhance reporting capabilities.
✨Engage with Stakeholders
This role requires collaboration with both technical and non-technical teams. Be ready to discuss how you've effectively communicated with stakeholders in the past, and how you bridge the gap between technical solutions and business needs.
