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- Tasks: Analyse large-scale IT asset data to provide actionable insights and support data migration.
- Company: Dynamic tech firm in Glasgow with a focus on IT Asset Management.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Why this job: Join a major programme and make a real impact with your data skills.
- Qualifications: Experience with large datasets, Python skills, and familiarity with IT asset management.
- Other info: Collaborative team environment with a focus on innovation and data quality.
The predicted salary is between 36000 - 60000 £ per year.
Help turn high-volume IT asset and configuration data into clear, practical insight for a major IT Asset Management programme.
I have an immediate opportunity for a Data Business Analyst to work on a major IT Asset Management programme using ServiceNow as the strategic IT Asset Management tool and CMDB for a corporate client in central Glasgow.
What you'll focus on:
- Analysing large-scale IT asset and configuration datasets to identify trends, issues and opportunities.
- Providing clear analysis and insight to the leadership team to inform decisions.
- Supporting the migration of data from multiple legacy systems into new IT Asset Management and CMDB solutions.
- Using Python to enhance analysis, automate repeatable tasks and improve data handling.
Key responsibilities:
- Explore and profile data from diverse systems and applications to assess data quality and completeness.
- Investigate data quality issues (including data quality-related IT asset problems) and propose practical remediation approaches.
- Work with IT Asset Management and CMDB stakeholders to understand data requirements and translate them into data analysis tasks.
- Structure and prepare datasets to support adoption of the ServiceNow-based IT Asset Management and CMDB solutions.
- Work closely with fellow data analysts to share findings, standardise approaches and support broader programme goals.
- Produce clear documentation and summaries of analysis, methods and findings for technical and non-technical audiences.
What we're looking for:
- Strong experience working with large-volume datasets in a business or IT context.
- Proven background as a Data Analyst, Data Engineer or similar data-focused role.
- Practical Python skills for analysis, data manipulation and automation.
- Experience of IT asset data (e.g. hardware, software, infrastructure), CMDB, ServiceNow, or similar technical datasets.
- Confidence working with data quality issues and remediation activities.
- Ability to turn complex data into clear, understandable insight for non-technical stakeholders.
- Comfortable working as part of a data-focused team on a major implementation or change programme.
- Structured, methodical approach with strong attention to detail.
Interested? Apply now for immediate consideration!
Data Business Analyst in Glasgow employer: Henderson Scott
Contact Detail:
Henderson Scott Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Business Analyst in Glasgow
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at local meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that Data Business Analyst role.
✨Tip Number 2
Prepare for those interviews by brushing up on your Python skills and data analysis techniques. We recommend practising common interview questions related to IT asset management and CMDB to show you’re the right fit for the job.
✨Tip Number 3
Don’t forget to showcase your past projects! Bring examples of how you’ve turned complex datasets into clear insights. We want to see how you’ve tackled data quality issues and what practical solutions you’ve implemented.
✨Tip Number 4
Finally, apply through our website! It’s the best way to ensure your application gets seen. We’re excited to see how you can contribute to our IT Asset Management programme!
We think you need these skills to ace Data Business Analyst in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with large datasets and any relevant tools like Python or ServiceNow. We want to see how your skills match the job description, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Data Business Analyst role. Share specific examples of how you've tackled data quality issues or provided insights that influenced decisions.
Showcase Your Analytical Skills: In your application, emphasise your analytical abilities. We’re looking for someone who can turn complex data into clear insights, so include examples of how you've done this in past roles. Make it relatable for both technical and non-technical audiences!
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and we’ll be able to review your application quickly. Don’t miss out on this opportunity!
How to prepare for a job interview at Henderson Scott
✨Know Your Data Inside Out
Before the interview, dive deep into the types of datasets you'll be working with. Familiarise yourself with IT asset data, CMDB concepts, and how ServiceNow operates. Being able to discuss specific examples of your experience with large-volume datasets will show that you’re not just a candidate, but a knowledgeable asset.
✨Show Off Your Python Skills
Since practical Python skills are a must for this role, prepare to discuss how you've used Python in past projects. Bring examples of how you've automated tasks or manipulated data. If possible, consider sharing a small code snippet or project that highlights your abilities—this can really set you apart!
✨Communicate Clearly
You’ll need to turn complex data into understandable insights for non-technical stakeholders. Practice explaining your past analyses in simple terms. Think about how you can convey technical information clearly and concisely, as this will be crucial in your role and during the interview.
✨Prepare for Data Quality Discussions
Data quality issues are a key part of this role, so be ready to discuss your experience with identifying and remediating these problems. Have a few examples in mind where you successfully tackled data quality challenges, and be prepared to suggest practical approaches to common issues.
