At a Glance
- Tasks: Lead a skilled team in creating advanced data visualisations and dashboards.
- Company: High-growth cyber security tech company protecting critical online services.
- Benefits: Competitive salary, hybrid working model, and opportunities for remote work.
- Other info: Join a culture that values ownership, curiosity, and smart engineering.
- Why this job: Work with cutting-edge tech on meaningful problems in a dynamic environment.
- Qualifications: Strong experience in Python, Grafana, and leading teams in an agile setting.
The predicted salary is between 95000 - 95000 £ per year.
Requirements
- Strong experience building dashboards and analytics in Python and ideally Grafana
- Proven background leading engineers in an agile environment
- Solid understanding of Linux and AWS
- Excellent communication skills; you can explain complex ideas simply
- A strong technical degree (Computer Science, Maths, Statistics, Engineering, or similar)
- Knowledge of networking protocols and how the internet actually works (nice to have)
- Experience with Splunk & SPL, SQL or similar data manipulation skills (nice to have)
- Exposure to network security products (nice to have)
- HTML, CSS, Java Script (nice to have)
- Data Science or Machine Learning experience (nice to have)
Responsibilities
- Leading a small, highly skilled team focused on network & security analytics
- Designing and building advanced Grafana dashboards running in Kubernetes
- Turning complex data into clear, insightful visualisations
- Developing and reviewing complex queries (Grafana, Splunk, Python)
- Mentoring engineers and shaping technical best practice
- Balancing hands‑on development with technical leadership and ownership
- Technologies
- AWS
- CSS
- Grafana
- Java Script
- Kubernetes
- Linux
- Machine Learning
- Network
- Python
- SQL
- Security
- Splunk
- Cloud
- More
We are a high‑growth cyber security technology company that protects some of the worlds most critical online services from large‑scale DDo S and application attacks.
Our sophisticated software is essential for keeping entire businesses online.
Were expanding our world‑class engineering team and looking for a Principal‑level expert to lead the way in network and security analytics.
We offer a hybrid working model for Edinburgh‑based engineers, with fully remote options available for the right candidate.
Join us to work with cutting‑edge tech on complex data and meaningful problems, in a culture that values ownership, curiosity, and smart engineering.
- last updated 27 week of 2026
- #J-18808-Ljbffr
StudySmarter Expert Advice🤫
We think this is how you could land Data Visualization Software Engineer - UK in London
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We think you need these skills to ace Data Visualization Software Engineer - UK in London
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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Craft a Tailored Cover Letter:For a full-time role at Bright Purple Resourcing, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
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How to prepare for a job interview at Bright Purple Resourcing
✨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.
