At a Glance
- Tasks: Analyse complex data to improve housing services and drive decision-making.
- Company: Join a forward-thinking organisation managing over 21,000 homes.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on digital transformation and career development.
- Why this job: Make a real difference in housing through data-driven insights and innovation.
- Qualifications: Experience in data analysis and tools like SQL or Python is essential.
The predicted salary is between 40000 - 50000 € per year.
The Role
Our client is looking for a skilled Data Business Analyst to support our Housing Directorate, managing over 21,000 homes across the city. This is a key role combining data analysis, business analysis and systems thinking, helping transform how data drives decision‑making, service delivery and investment planning. You will work across business and technical teams to turn complex datasets into clear, actionable insights, improving housing services and resident outcomes.
Key Responsibilities
- Analyse complex housing and asset data to support strategic planning and decision‑making
- Identify data quality issues, duplication and process inefficiencies across services
- Support asset lifecycle planning and investment programmes using data‑led insights
- Develop dashboards, reports, heatmaps and performance metrics
- Enable predictive maintenance and risk‑based service delivery models
- Work closely with Housing, IT and stakeholders to improve systems and data usage
- Support digital and transformation programmes across the directorate
- Produce business analysis outputs including process maps, requirements and project documentation
- Ensure compliance with GDPR, data governance and ICT security standards
- Liaise with system providers on improvements, upgrades and issue resolution
About You
Essential Experience
- Strong background in data analysis and business analysis
- Experience using tools such as SQL, Python, R or similar
- Proven experience working with large, complex datasets
- Ability to translate technical insights into clear, non‑technical recommendations
- Experience delivering data‑driven change or transformation initiatives
- Strong stakeholder engagement across technical and non‑technical teams
Desirable
- Experience within housing, asset management or local government
- Knowledge of Building Safety, Decent Homes or housing regulations
- Familiarity with NoSQL (e.g. MongoDB)
- Understanding of data standards (GDS, governance frameworks)
If you are interested in this role please send your updated CV in the first instance.
Data Business Analyst employer: Supply Staff Limited
Our client is an exceptional employer, offering a dynamic work environment where data-driven decision-making shapes the future of housing services. With a strong focus on employee growth and development, team members are encouraged to enhance their skills through collaboration across business and technical teams, while contributing to meaningful projects that directly impact over 21,000 homes in the city. The inclusive culture fosters innovation and supports a commitment to improving resident outcomes, making it a rewarding place to build a career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Business Analyst
✨Tip Number 1
Network like a pro! Reach out to people in the housing and data sectors on LinkedIn. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those related to housing or asset management. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis scenarios. Think about how you’d tackle issues like data quality or predictive maintenance, and be ready to share your thought process.
✨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!
We think you need these skills to ace Data Business Analyst
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Business Analyst role. Highlight your experience with data analysis and any relevant tools like SQL or Python. We want to see how your skills match what we're looking for!
Showcase Your Achievements:Don’t just list your responsibilities; showcase your achievements! Use specific examples of how you've turned complex datasets into actionable insights. This will help us see the impact you've made in previous roles.
Keep It Clear and Concise:When writing your application, keep it clear and concise. Avoid jargon and make sure your recommendations are easy to understand. We appreciate straightforward communication that gets to the point!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Supply Staff Limited
✨Know Your Data Tools
Make sure you brush up on your skills with SQL, Python, or R before the interview. Be ready to discuss how you've used these tools in past projects, especially when analysing complex datasets. This will show that you can hit the ground running!
✨Understand the Housing Sector
Familiarise yourself with key concepts in housing and asset management. Knowing about Building Safety and Decent Homes regulations can give you an edge. It shows you're not just a data whiz but also understand the context of your work.
✨Prepare for Scenario Questions
Expect questions that ask you to solve hypothetical problems using data analysis. Think about how you would identify data quality issues or improve service delivery models. Practising these scenarios can help you articulate your thought process clearly.
✨Engage with Stakeholders
Be prepared to discuss how you've worked with both technical and non-technical teams in the past. Highlight your communication skills and how you translate complex data insights into actionable recommendations. This is crucial for the role!
