At a Glance
- Tasks: Extract and analyse data to generate insights for housing strategies and policies.
- Company: Join a dynamic team focused on improving social housing through data.
- Benefits: Competitive pay, engaging work environment, and opportunities for professional growth.
- Other info: Collaborative culture with a focus on continuous improvement and innovation.
- Why this job: Make a real difference in housing by turning data into actionable insights.
- Qualifications: Experience with data analysis and ability to communicate with diverse audiences.
The predicted salary is between 30000 - 40000 € per year.
Essentially to Note: Knows about social housing and empty homes or at least understand letting properties as a data analyst. Have the ability to talk to non-data users. Got to be client facing and engaging to explain what they are doing and how to use information. Need to understand how to use NEC housing management system. Don't have to be an advanced user of Power BI and Azure Data Bricks. Based at Westminster Bridge Road - near Waterloo for the office.
Job Description:
- Extract, clean, and transform complex datasets from various sources to perform insightful analyses, uncover patterns, and identify opportunities for improvement.
- Interpret data to create meaningful insights, visualisations, and reports that support key stakeholders in making informed decisions.
- Monitor trends, demographic shifts, and regulatory changes to provide proactive recommendations for adapting housing processes, strategies and policies.
- Develop and maintain key performance indicators (KPIs).
- Work closely with cross-functional teams including housing operations, finance, IT, and Business Analysts to align data analysis efforts with organisational objectives.
- Ensure data accuracy, consistency, and integrity by implementing quality control measures and adhering to data governance practices.
- Produce regular and ad-hoc reports, dashboards, and presentations to communicate insights, trends, and recommendations to both technical and non-technical audiences.
- Identify opportunities for process improvement, automation, and innovation in data analysis and reporting methodologies.
- Manage and improve a suite of products that exist in PowerBI, Tableau, and other tools, which provide ongoing monitoring of key performance indicators for various teams and stakeholders throughout the company.
To find out more information please contact Recruitment is done in line with safe recruitment practices. We are an equal opportunity agency.
SQL Data & Insight Analyst in Wishaw employer: 4Recruitment Services
As a SQL Data & Insight Analyst at our Westminster Bridge Road office near Waterloo, you will thrive in a dynamic work culture that values collaboration and innovation. We offer competitive pay, opportunities for professional growth, and a commitment to employee development, ensuring you can enhance your skills while making a meaningful impact in the social housing sector. Join us to be part of a team that prioritises data integrity and insightful analysis, all while enjoying the vibrant atmosphere of central London.
StudySmarter Expert Advice🤫
We think this is how you could land SQL Data & Insight Analyst in Wishaw
✨Tip Number 1
Get to know the company and its culture before your interview. Research their projects, especially in social housing and data analysis. This will help you connect your skills with their needs and show that you're genuinely interested.
✨Tip Number 2
Practice explaining complex data insights in simple terms. Since you'll be talking to non-data users, being able to break down your analyses into relatable concepts is key. Try role-playing with a friend to get comfortable.
✨Tip Number 3
Prepare some questions for your interviewers about their current data challenges or projects. This shows that you're proactive and ready to engage with their team. Plus, it gives you a chance to demonstrate your problem-solving mindset.
✨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 take that extra step to connect with us directly.
We think you need these skills to ace SQL Data & Insight Analyst in Wishaw
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the SQL Data & Insight Analyst role. Highlight your experience with data analysis, especially in social housing or property letting, and don’t forget to mention any relevant tools like Power BI or Azure Data Bricks.
Craft a Compelling Cover Letter:Use your cover letter to showcase your personality and explain why you’re passionate about data analysis. Talk about how you can engage with non-data users and make complex information accessible to everyone.
Showcase Your Communication Skills:Since this role is client-facing, it’s crucial to demonstrate your ability to communicate insights effectively. Include examples of how you've successfully explained data findings to non-technical audiences in the past.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get you on the path to joining our team!
How to prepare for a job interview at 4Recruitment Services
✨Know Your Data
Make sure you brush up on your knowledge of data extraction, cleaning, and transformation. Be ready to discuss how you've handled complex datasets in the past and how you can apply that experience to the role.
✨Understand the Client's Needs
Since this role is client-facing, practice explaining technical concepts in simple terms. Think about how you would communicate insights to someone without a data background, and prepare examples of how you've done this before.
✨Familiarise Yourself with Tools
While you don’t need to be an expert in Power BI or Azure Data Bricks, having a basic understanding of these tools will help. Consider doing a quick tutorial or two to get comfortable with their functionalities.
✨Show Your Collaborative Spirit
This position involves working closely with various teams. Prepare to share examples of how you've successfully collaborated with others in the past, especially in cross-functional settings. Highlight your ability to align data analysis with organisational goals.
