Senior Data Engineer

London
1 year ago
Applications closed

Related Jobs

View all jobs

AI Senior Product Manager

Senior Backend AI Engineer

Senior AI/ML Engineer

Senior Software Engineer

Senior Python Engineer

Senior FGPA Engineer

Position: Senior Data Engineer

Salary: £55,000 - £65,00

Location: Hybrid - Bristol, Manchester, or London
Security Requirement: SC Clearance to start and be willing / able to obtain DV Clearance

We are seeking Data Engineers, with a keen interest / experience in AI /ML and strong proficiency in Python Scripting. To join our Consultancy client working on meaningful projects in the Defence and Security sector.

Required Experience:

End-to-End Data Development: Strong experience with data pipelines, ETL processes, and workflow orchestration, demonstrating best practices across tech stacks.
Strong Python Skills
Diverse Data Handling: Familiarity with batch, streaming, real-time, and unstructured data sources.
Architectural Design & Systems Thinking: Ability to design and build scalable, high-performance data solutions.
Data Modelling & Warehouse Design: Proficiency in data modelling, warehouse design, and database optimization, with examples of logical and physical models.
Distributed Data Systems: Experience in deploying, managing, and tuning distributed systems for optimal reliability and performance.
Coding & Development Practices: Demonstrated coding expertise with modular, reusable, and efficient code in various languages.
Development Lifecycle: Understanding of SDLC, CI/CD pipelines, and version control.
Data Governance & Security: Knowledge of data security, governance, metadata management, and master data principles.Key Responsibilities:

As a Senior Data Engineer, you'll bridge the gap between client needs and technical solutions, creating data pipelines that ingest, transform, and enrich large data volumes. You'll have client-facing responsibilities, delivering high-quality data solutions in multi-disciplinary teams across industries.

In this consulting role, your responsibilities will vary depending on client engagement focus and your skillset, but will often include:

Data Engineering & AI Integration: Apply data engineering tools, integration frameworks, and query engines to create high-quality, standardised data for AI applications and reporting.
Data Pipeline Development: Design and implement robust data pipelines and stores in collaboration with other engineers and developers.
Innovative Problem Solving: Bring fresh approaches to challenging data engineering problems.
Architecture for Scale: Design scalable, complex data architectures that provide cross-team value.
Data Modelling & Governance: Establish standards in logical and physical data modelling and data governance.
Distributed Computing: Employ parallel processing, streaming, and batch workflows to manage large data volumes effectively.
ETL & Workflow Automation: Build ETL processes and automated workflows for efficient data movement.
System Optimization: Tune data systems for performance, scalability, and monitoring.
Data Security: Apply best practices for information security, including encryption and data anonymity for sensitive data assets.
Data Governance & Quality: Manage metadata, data lineage, and data quality standards.If you're passionate about using data engineering and AI to solve complex problems in the Defence and Security sector, we'd love to hear from you!

People Source Consulting Ltd is acting as an Employment Agency in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas

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.

Where to Advertise Edge Computing Jobs in the UK (2026 Guide)

Advertising edge computing jobs in the UK requires a different approach to most technical hiring. Edge computing sits at the intersection of embedded systems, networking, cloud infrastructure and real-time data processing — and the professionals who specialise in it are a small, highly technical community not well served by general job boards. Candidates with genuine edge and IoT expertise are rarely browsing general platforms, and roles in this space are frequently misunderstood or miscategorised by non-specialist recruiters. This guide, published by EdgeComputingJobs.co.uk, covers where to advertise edge computing roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

New Edge Computing Employers to Watch in 2026: UK and Global Companies Shaping Edge Innovation

Edge computing is transforming how data is processed by bringing compute power closer to the source of generation. With the proliferation of Internet of Things (IoT), real‑time analytics, autonomous systems, and latency‑sensitive applications, edge computing has moved from a niche discipline to a core component of digital infrastructure. In 2026, organisations that specialise in or heavily invest in edge computing are expanding their teams to build distributed systems, real‑time analytics platforms, and edge‑optimised AI. For professionals exploring opportunities on www.EdgeComputingJobs.co.uk , understanding which employers are growing, winning contracts, or securing investment is essential. This article highlights the new and high‑growth edge computing employers to watch in 2026, including UK startups, international innovators with a UK presence, and established companies shifting strategy toward edge.

How Many Edge Computing Tools Do You Need to Know to Get an Edge Computing Job?

If you’re trying to start or grow a career in edge computing, it can feel like you’re navigating a maze of tools, frameworks and platforms — Kubernetes, Docker, IoT frameworks, AWS Greengrass, Azure IoT Edge, OpenShift, TinyML toolkits, networking orchestration, real-time streaming frameworks, and on it goes. Scroll job boards and community forums and it’s easy to conclude that unless you master every buzzword imaginable, you’ll never get a job. Here’s the honest truth most edge computing hiring managers won’t necessarily say out loud: 👉 They don’t hire you because you know every edge computing tool — they hire you because you can solve real system problems using the tools you know. Tools matter, yes — but only when they support clear outcomes: reliable systems, performance at scale, secure edge deployments and real business value. So how many edge computing tools do you actually need to know to secure a job? For most edge computing roles, the answer is fewer than you think — and a lot clearer when sorted by fundamentals and roles. This guide shows you what matters, what doesn’t, and how to focus your time wisely so you come across as capable, confident and employable.