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 SQL employer: ALOIS UK
Join a forward-thinking company that values innovation and collaboration, where as a Business Intelligence Engineer SQL, 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. Located in a vibrant area, we offer a dynamic environment that encourages creativity and teamwork, making us an excellent employer for those seeking rewarding careers in data and analytics.
StudySmarter Expert Advice🤫
We think this is how you could land Business Intelligence Engineer SQL
✨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 help you land that Business Intelligence Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Power BI reports and AWS data pipelines. We want to see your hands-on experience, so don’t be shy about sharing your projects with potential employers.
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL and AWS knowledge, and be ready to discuss how you’ve tackled real-world problems. We recommend practicing common interview questions related to data engineering and AI initiatives.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals like you. By applying directly, you’ll have a better chance of getting noticed by our hiring team and landing that dream job.
We think you need these skills to ace Business Intelligence Engineer SQL
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 Engineering capabilities and any relevant AI/ML exposure to catch our eye!
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're the perfect fit for this role. Share specific examples of your work with Power BI and AWS services, and how you've contributed to data-driven projects in the past.
Showcase Your Technical Skills:Don’t shy away from listing your technical proficiencies! We want to see your experience with SQL, Power BI, and AWS services clearly laid out. If you’ve worked with DAX or Python, make sure to mention it!
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 this exciting opportunity!
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 Athena, S3, 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. The more specific examples you can provide, the better!
✨Showcase Your AI/ML Exposure
Even if AI/ML isn't your main focus, it's crucial to demonstrate your practical exposure to these technologies. Think about any projects where you've worked with AI services or supported ML pipelines. Be prepared to explain how these experiences can contribute to the role.
✨Prepare for Stakeholder Engagement
This role requires collaboration with both technical and non-technical stakeholders. Practice explaining complex technical concepts in simple terms. You might be asked how you gather requirements or translate business needs into technical solutions, so have a few scenarios ready to share.
✨Emphasise Your Problem-Solving Skills
The interviewers will likely want to see how you approach challenges. Prepare to discuss specific problems you've encountered in your previous roles and how you solved them, particularly in relation to data engineering and analytics. Highlight your analytical mindset and hands-on approach!
