At a Glance
- Tasks: Analyse vendor licensing data and create insightful reports to drive smarter business decisions.
- Company: Join a fast-growing tech company in the cyber resilience space with a collaborative culture.
- Benefits: Competitive salary, remote work, and opportunities for professional growth.
- Other info: Quarterly face-to-face meetings and a proactive approach to building processes.
- Why this job: Make an impact by turning complex data into actionable insights in a dynamic environment.
- Qualifications: Experience in data analysis, strong skills in SQL, Python, and Power BI.
VIQU are partnering with a fast-growing technology organisation operating within the cyber resilience and managed services space. They are seeking a Data Analyst to join their commercial function and analyse vendor licensing data, consumption trends, and commercial performance across a multi-million-pound technology environment. This newly created role offers the opportunity to build reporting models, improve business visibility, and turn complex data into actionable insight. Working closely with commercial, finance, sales, and operational teams, this role will support smarter licensing decisions, protect margins, and improve forecasting accuracy as the business continues to grow.
Key Responsibilities of the Data Analyst:
- Analyse vendor licensing data, customer consumption, and entitlement usage
- Maintain accurate customer-to-licensing mappings across vendor environments
- Build reporting models to track utilisation, forecasting, and commercial performance
- Identify licensing risks, cost-saving opportunities, and margin improvements
- Create dashboards and reports using tools such as Power BI and Excel
- Support vendor renewals with data-driven insights and analysis
- Provide commercial reporting to senior stakeholders across the business
- Improve processes and develop new analytical frameworks from the ground up
Key Experience Required of the Data Analyst:
- Experience within a Data Analyst, Commercial Analyst, FinOps, or similar analytical role
- Strong skills in SQL, Python, Power BI, and advanced Excel
- Experience analysing complex datasets and producing clear business insights
- Commercial mindset with an interest in how data impacts decision-making
- Technology industry experience is highly desirable, ideally within SaaS, cloud, MSP, or licensing environments
- Exposure to vendor licensing, consumption tracking, or software asset management would be beneficial
- Strong communication skills with the ability to present findings and challenge assumptions
- Proactive approach with the ability to build processes and reporting from scratch
- Experience using AI/LLM tools for analysis would be advantageous
Apply now to speak with VIQU IT in confidence, or reach out to Katie Dark via the VIQU IT website.
Data Analyst - Vendor Licensing employer: VIQU IT
At VIQU IT, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture in the heart of Birmingham. Our commitment to employee growth is evident through continuous professional development opportunities and a supportive environment that encourages strategic thinking and transformation. With competitive salaries and a focus on work-life balance, we empower our team to thrive while making a meaningful impact in the technology sector.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst - Vendor Licensing
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We think you need these skills to ace Data Analyst - Vendor Licensing
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at VIQU IT
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
