At a Glance
- Tasks: Design and develop AWS data pipelines while enhancing reporting and analytics capabilities.
- Company: Join a forward-thinking tech company driving AI and data innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with a mix of hands-on engineering and strategic development.
- Why this job: Be at the forefront of AI-driven initiatives and modern data solutions.
- Qualifications: Degree in Computing or related field; experience in data engineering and BI.
The predicted salary is between 55000 - 65000 £ 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.
Engineer building technology employer: ALOIS UK
Join a forward-thinking company that values innovation and collaboration, where as an Engineer in Building Technology, you will be at the forefront of developing cutting-edge data solutions. With a strong emphasis on employee growth, we offer extensive training opportunities in AWS and AI technologies, fostering a culture of continuous learning and professional development. Located in a vibrant area, our workplace promotes a healthy work-life balance and encourages teamwork, making it an excellent environment for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Engineer building technology
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even local tech events. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Show Off Your Skills
Create a portfolio showcasing your projects, especially those involving AWS, Power BI, or AI/ML. This is your chance to demonstrate your hands-on experience and problem-solving skills. Make sure to highlight any relevant work that aligns with the job description!
✨Ace the Interview
Prepare for technical interviews by brushing up on your SQL, AWS services, and Power BI skills. Practice common interview questions and be ready to discuss how you've tackled challenges in past projects. Confidence is key, so show them what you’ve got!
✨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, it shows you’re genuinely interested in joining our team and contributing to exciting data and AI initiatives.
We think you need these skills to ace Engineer building technology
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, Python, and any cloud-based AI services. Be clear about your hands-on experience and how it relates to the role.
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’re well-versed in AWS services like Athena, S3, and Redshift, as well as Power BI. Brush up on your SQL skills and be ready to discuss how you've used these technologies in past projects. The more specific examples you can provide, the better!
✨Showcase Your AI/ML Exposure
Even if AI/ML isn't your main focus, be prepared to talk about any relevant experience you have. Whether it’s working with cloud-based AI services or supporting ML pipelines, make sure to highlight how you’ve contributed to AI-driven initiatives.
✨Prepare for Stakeholder Engagement
This role involves collaborating with both technical and non-technical teams. Think of examples where you’ve successfully gathered requirements or translated business needs into technical solutions. Being able to communicate effectively is key!
✨Demonstrate Your Problem-Solving Skills
Be ready to tackle some hypothetical scenarios during the interview. Show how you approach problem-solving, especially in fast-paced environments. Highlight your analytical mindset and hands-on engineering approach to impress the interviewers.
