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- Tasks: Lead data management and optimisation, ensuring accuracy and security across the organisation.
- Company: Join a legacy organisation committed to service, community impact, and environmental sustainability.
- Benefits: Enjoy 33 days of leave, competitive salary, pension contributions, and discounts at various businesses.
- Why this job: Be part of a diverse culture that values innovation and collaboration while making a real impact.
- Qualifications: Degree in relevant fields preferred; passion for data and experience with ETL processes required.
- Other info: Opportunities for career progression and a supportive work environment await you!
The predicted salary is between 43200 - 72000 £ per year.
This organisation has a proud legacy of growth and innovation, driven by a deep commitment to outstanding service and community impact. Today, that dedication is stronger than ever. With a clear mission and a culture that champions diversity, inclusion, and equal opportunity, they’re building a future where everyone can thrive. Safety is at the heart of everything they do, and they’re leading the way in environmental sustainability.
You’ll take the lead in managing and optimising how data is used across the organisation, ensuring its accuracy, integrity, and security. From overseeing data governance to enabling the use of advanced tools like Language Models, your work will help turn complex data into meaningful insights. Collaboration is central to this role - you’ll work closely with cross-functional teams to build and maintain robust data systems and infrastructure. Your contributions will directly support smarter decision-making and drive innovation across the business.
What you’ll need to succeed:
- A degree in Computer Science, Information Technology, Mathematics, Statistics, or a related field. (Not a must but beneficial)
- A genuine passion for data - its potential, its impact, and how to harness it effectively.
- Hands-on experience supporting and improving ETL processes.
- Strong proficiency in SQL and other programming languages used for data analysis.
- Advanced expertise in Power BI or similar data visualisation tools.
- Solid understanding of machine learning platforms and algorithms.
- Vision, insight, and the drive to lead change and deliver meaningful results.
What you’ll get in return:
- A competitive salary
- 33 days of annual leave
- Fantastic pension contributions
- Clear paths for career progression
- A generous pension scheme
- Concessionary travel benefits for employees and their families
- Discounts on food & drink and at various businesses
- On-site café
- Electric car scheme
- Free parking
- The list goes on!
If you’re interested in this role, click ‘apply now’ to forward an up-to-date copy of your CV, or call us now. If this job isn’t quite right for you, but you are looking for a new position, please contact us for a confidential discussion about your career.
Senior Data Manager employer: Hays
Contact Detail:
Hays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Manager
✨Tip Number 1
Familiarise yourself with the latest trends in data management and visualisation tools. Being well-versed in platforms like Power BI and machine learning algorithms will not only boost your confidence but also demonstrate your commitment to staying ahead in the field.
✨Tip Number 2
Network with professionals in the data management space. Attend industry events, webinars, or local meetups to connect with others who share your passion for data. This can lead to valuable insights and potential referrals that could help you land the job.
✨Tip Number 3
Showcase your hands-on experience with ETL processes during interviews. Be prepared to discuss specific projects where you've optimised data workflows, as this will highlight your practical skills and ability to contribute to the organisation's goals.
✨Tip Number 4
Emphasise your collaborative skills when speaking with potential employers. Since this role involves working closely with cross-functional teams, demonstrating your ability to communicate effectively and lead change will set you apart from other candidates.
We think you need these skills to ace Senior Data Manager
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data management, ETL processes, and proficiency in SQL. Use specific examples that demonstrate your ability to optimise data usage and ensure its integrity.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and how it can drive innovation. Mention your hands-on experience with data visualisation tools like Power BI and your understanding of machine learning platforms.
Showcase Collaboration Skills: Since collaboration is key in this role, include examples in your application that illustrate your ability to work with cross-functional teams. Highlight any projects where you successfully partnered with others to achieve data-driven results.
Highlight Continuous Learning: Mention any relevant courses, certifications, or workshops you've completed that relate to data management and analysis. This shows your commitment to staying updated in the field and your drive to lead change.
How to prepare for a job interview at Hays
✨Show Your Passion for Data
Make sure to express your genuine enthusiasm for data and its potential during the interview. Share specific examples of how you've harnessed data to drive insights or improve processes in your previous roles.
✨Demonstrate Technical Proficiency
Be prepared to discuss your hands-on experience with ETL processes, SQL, and data visualisation tools like Power BI. You might be asked to solve a technical problem on the spot, so brush up on your skills beforehand.
✨Highlight Collaboration Skills
Since collaboration is key in this role, come ready with examples of how you've successfully worked with cross-functional teams. Discuss any challenges you faced and how you overcame them to achieve common goals.
✨Prepare for Questions on Machine Learning
Given the emphasis on machine learning platforms and algorithms, be ready to discuss your understanding of these concepts. You could be asked about specific algorithms you've used or how you've applied machine learning in past projects.
