Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Software Engineer - EMEA (Europe) Based

Nucleus Security
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer - Data Engineering Team

Senior Data Engineer - Scala/Spark

Senior Software and Data Engineer

Senior Data Engineer / Trading Software Engineer, Autobidder

Senior Data Engineer I

Senior Data Engineer in London - Zenobē

Senior Software Engineer - EMEA Region Are you looking for more in life than just building another web app? Does upending cyber security resonate with you? We're a rapidly expanding cybersecurity startup revolutionizing vulnerability management for organizations of all sizes. For our customers, vulnerability management has always been a game of catch-up, with limited asset coverage and manual processes. Nucleus' primary mission is to create a fast, scalable platform that not only addresses these challenges but also makes vulnerability management simple, fun, and effortless. Currently, we're looking for a passionate Senior PHP Data Engineer to join our growing team of engineers.  This is a remote role based in the EMEA region (Europe). What You Will Do:  The following skills and experience are key to succeeding in this role:  Strong background in data analytics, data science, and/or data warehousing. Proficiency in working with relational databases, including MySQL or PostgreSQL. Experience in an object-oriented programming language such as PHP or Java. Experience working in a test-driven environment and writing unit and integration tests Proven ability in technical troubleshooting. Capable of working independently as well as collaboratively with teams across different time zones. Preferred Qualifications:  Experience working with vulnerability scanning technologies on any part of the tech stack (e.g., SCA, SAST, DAST, IAST, VM Scanning, Container, etc.)  Experience with column store databases and columnar data, especially using SingleStore/MEMSQL Experience working in cloud environments, ideally AWS.  Familiarity with Agile/Scrum methodologies in a professional setting. Experience maintaining applications on Linux platforms in cloud environments. Experience with modern versions of PHP, and the Zend and Laminas Frameworks Major or minor in a mathematics discipline Improve key components of the application to enable data scalability. Why You Should Be Excited     Nucleus is a truly unique solution that’s defining a market AND making an actual impact.    We’re biased, but you will get to work with one of the best teams in security. We have a lot to get done and we work extremely hard, but we have fun in the process.    Outstanding benefits - flexible PTO, generous education and training budget, fully remote… just to start       Additional Information   At Nucleus we are committed to achieving excellence in our field by combining diversity, collaboration, teamwork, and pride in our work. All qualified applicants will receive consideration for employment without regard to race, sex, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or disability.    Powered by JazzHR

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.