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

Apply Now

Data Engineer

Adarga Ltd
City of London
3 days ago
Create job alert
About Adarga

Adarga is the UK’s only sovereign Defence Tech company specialising in applied AI solutions across intelligence, operations and planning. In an era of information overload, Adarga delivers technology that enables our mission partners to act with speed, clarity and confidence. By unlocking the value of their data, we help our partners make better decisions that achieve mission-critical outcomes.

Our team is a hybrid of domain specialists and technologists. We believe this layering of experience is key to building cutting edge AI that is operationally relevant, solving real problems, to drive real outcomes.

This is a unique time to join Adarga. With our foundations set in NLP, computational linguistics and graph technology we now draw on the latest ideas in generative AI and knowledge representation, as we set our sights firmly on defining and building the next era of sovereign AI capability for mission partners across the Defence and National Security sectors.

To work at Adarga you have to care deeply about the mission. We exist to support those with the ultimate task: upholding the liberties and values that define our society. In today’s contested, multipolar world, this cannot be taken for granted.

We want people who are comfortable with uncertainty, who want to own decisions, who want to drive a vision. If that is you, get in touch!

If you don\'t match all the skills and qualifications but care about our mission then we\'d encourage you to back yourself and apply anyway. We all learn by doing

About the role:

This is a rare opportunity to design and build a first-of-its-kind adaptive intelligence platform designed for mission-critical environments. You’ll be working at the intersection of real-time data processing, multimodal ingestion, adaptive knowledge representation, and composable services, all built to operate across the most demanding deployment contexts (on-prem, cloud, and/or edge).

You’ll work side by side with defence and intelligence domain experts to drive rapid iteration cycles, ensuring what you build is grounded in real operational need. It’s a greenfield build where you’ll have full ownership of how core components come together, (e.g. ingestion pipelines, ontological reasoning layers, reusable capability services,) with the freedom to make smart, scalable technical decisions early. There’s no legacy stack and no hand-holding.

You’ll have the freedom to move fast, own critical decisions, and build a platform that could reshape how intelligence is used in modern operations.

Responsibilities:

  • Architect and implement core infrastructure for a high-performance, adaptive intelligence platform.
  • Build robust, scalable pipelines for ingesting and transforming multimodal data in real time.
  • Design systems for knowledge representation and ontological reasoning that can adapt as information evolves.
  • Develop composable services capable of deployment across cloud, edge, and on-prem environments.
  • Collaborate with domain experts and end users to deeply understand operational constraints and mission needs.
  • Lead technical design and decision-making while remaining hands-on in building and shipping code.
  • Ensure systems are secure, reliable, and maintainable under demanding operational conditions.
  • Drive a culture of pragmatic innovation, balancing rapid iteration with robust engineering standards.

Skills and Qualifications:

  • A strong systems thinker and engineer with a track record of designing and delivering complex platforms.
  • Proven experience building distributed systems, data pipelines, or infrastructure for mission- or safety-critical environments.
  • Deep proficiency in at least one modern systems-level or backend programming language (e.g. Python, Rust, Go, or similar) with the ability to design, implement, and optimise performant, reliable software.
  • Experience architecting systems that handle diverse data types—text, geospatial, sensor, temporal, etc.
  • Familiarity with container orchestration and deployment across varied infrastructure contexts (e.g. Kubernetes, edge compute, air-gapped environments).
  • Comfortable working autonomously and making early design decisions that will shape the future of the platform.
  • A collaborative mindset—able to work closely with experts across AI, product, and defence domains.
  • A growth-oriented engineer who thrives in ambiguity, iterates fast, and builds with care.

Interview Process

  • Phone Interview – Remote (30 mins)
  • Technical Interview – Remote/In person (1 h)
  • Final Interview – Onsite (1 h)

Successful applicants may be required to undergo national security vetting upon appointment or during employment in this role. Applicants must meet the security requirements set out by UK Security Vetting (UKSV), and understand what is required in the associated UKSV: Vetting Guidance before they can be appointed.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.

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.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.