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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 on food and travel.
- Why this job: Be part of a diverse culture that values innovation and collaboration while making a real impact.
- Qualifications: Degree in a related field is beneficial; passion for data and experience with ETL processes required.
- Other info: Work closely with cross-functional teams and utilise advanced tools like Language Models.
The predicted salary is between 28800 - 48000 £ 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.
Contact Detail:
Hays Specialist Recruitment Limited 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 or webinars where you can connect with others who work in similar roles. This can lead to valuable insights and potentially even referrals for the position you're interested in.
✨Tip Number 3
Showcase your passion for data by engaging in relevant projects or contributing to open-source initiatives. This hands-on experience can set you apart from other candidates and provide concrete examples of your skills during interviews.
✨Tip Number 4
Prepare for the interview by thinking about how you can contribute to the organisation's mission of community impact and sustainability. Be ready to discuss how your expertise in data can drive innovation and support smarter decision-making within the company.
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 collaborated to achieve data-driven results.
Proofread and Edit: Before submitting your application, carefully proofread your documents for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Senior Data Manager.
How to prepare for a job interview at Hays Specialist Recruitment Limited
✨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 in previous roles to drive insights and decision-making.
✨Demonstrate Technical Proficiency
Be prepared to discuss your hands-on experience with ETL processes, SQL, and data visualisation tools like Power BI. Consider bringing along a portfolio or examples of your work to showcase your skills.
✨Highlight Collaboration Skills
Since collaboration is key in this role, be ready to talk about your experience working with cross-functional teams. Share stories that illustrate your ability to communicate effectively and build strong relationships.
✨Prepare for Questions on Machine Learning
Given the emphasis on machine learning platforms and algorithms, brush up on your knowledge in this area. Be ready to discuss any relevant projects or experiences where you've applied machine learning techniques.
