C++ Software Engineer

Great Chesterford
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer x1/ Data Engineer x1 (Financial Services)

Graduate Data Engineer

GCP Data Engineer

Data Engineer

Senior Data Engineer

Head of DevOps and DataOps

About the Company

Our client is an established Aero/ Defence Technology SME based in the wider Cambridge area.

They are a leading designer and manufacturer of radar systems whose patented and industry-leading radar technologies are deployed in over 35 countries for applications including border surveillance, perimeter security, and infrastructure monitoring.

The Opportunity

Our client is expanding its software engineering team to support a demanding and ambitious product roadmap.

The role involves the design and development of software across the radar systems portfolio, including external control systems and system interfaces. This also includes the development of integrations with third-party security and surveillance platforms, as well as improvements in user-facing software capabilities and overall user experience.

Key Responsibilities



Design and develop software for the company’s radar systems.

*

Create software interfaces for integration with third-party surveillance and security systems.

*

Enhance and improve software functionality with a focus on user experience.

*

Contribute to the continual improvement of software engineering practices within the organisation.

Required Qualifications & Skills

*

Proficient in C++ (Essential)

*

Demonstrable industry experience of software development.

*

Strong understanding and hands-on experience with object-oriented software design.

*

Ability to work effectively in a cross-functional team environment - Excellent written and verbal communication skills.

*

Analytical and creative problem-solving abilities.

*

Comfortable working directly with end customers and users.

Preferred Qualifications & Experience

*

Degree in software engineering, computer science, or an engineering/science discipline with a software focus.

*

Experience developing command and control (C2) software for security or defence applications.

*

Familiarity with Geographic Information System (GIS) data and its manipulation.

*

Experience working with SQL databases.

*

Knowledge of user interface (UI) design and user experience (UX) best practices.

*

Understanding of real-time software development principles.

*

Experience with embedded Linux systems and embedded software development.

*

Exposure to machine learning techniques and classification methodologies.

*

Familiarity with Python or similar scripting languages.

*

Strong mathematical and statistical analysis skills.

*

Valid driver’s licence and passport for occasional business travel related to projects

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.

How to Write a Data Engineering Job Ad That Attracts the Right People

Data engineering is the backbone of modern data-driven organisations. From analytics and machine learning to business intelligence and real-time platforms, data engineers build the pipelines, platforms and infrastructure that make data usable at scale. Yet many employers struggle to attract the right data engineering candidates. Job adverts often generate high application volumes, but few applicants have the practical skills needed to build and maintain production-grade data systems. At the same time, experienced data engineers skip over adverts that feel vague, unrealistic or misaligned with real-world data engineering work. In most cases, the issue is not a shortage of talent — it is the quality and clarity of the job advert. Data engineers are pragmatic, technically rigorous and highly selective. A poorly written job ad signals immature data practices and unclear expectations. A well-written one signals strong engineering culture and serious intent. This guide explains how to write a data engineering job ad that attracts the right people, improves applicant quality and positions your organisation as a credible data employer.

Maths for Data Engineering Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data engineering jobs in the UK, maths can feel like a vague requirement hiding behind phrases like “strong analytical skills”, “performance mindset” or “ability to reason about systems”. Most of the time, hiring managers are not looking for advanced theory. They want confidence with the handful of maths topics that show up in real pipelines: Rates, units & estimation (throughput, cost, latency, storage growth) Statistics for data quality & observability (distributions, percentiles, outliers, variance) Probability for streaming, sampling & approximate results (sketches like HyperLogLog++ & the logic behind false positives) Discrete maths for DAGs, partitioning & systems thinking (graphs, complexity, hashing) Optimisation intuition for SQL plans & Spark performance (joins, shuffles, partition strategy, “what is the bottleneck”) This article is written for UK job seekers targeting roles like Data Engineer, Analytics Engineer, Platform Data Engineer, Data Warehouse Engineer, Streaming Data Engineer or DataOps Engineer.

Neurodiversity in Data Engineering Careers: Turning Different Thinking into a Superpower

Every modern organisation runs on data – but without good data engineering, even the best dashboards & machine learning models are built on sand. Data engineers design the pipelines, platforms & tools that make data accurate, accessible & reliable. Those pipelines need people who can think in systems, spot patterns in messy logs, notice what others overlook & design elegant solutions to complex problems. That is exactly why data engineering can be such a strong fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & considering a data engineering career, you might have heard comments like “you’re too disorganised for engineering”, “too literal for stakeholder work” or “too distracted for complex systems”. In reality, the traits that can make traditional office environments hard often line up beautifully with data engineering work. This guide is written for data engineering job seekers in the UK. We’ll cover: What neurodiversity means in a data engineering context How ADHD, autism & dyslexia strengths map to common data engineering tasks Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data engineering – & how to turn “different thinking” into a genuine professional superpower.