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

Apply Now

Enterprise Data Architect

developrec
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Science Manager - Marketing & Customer Generative AI Enterprise Architect

Graduate Data Scientist - Digital Enterprise

Microsoft Fabric Consultant | DataOps | £75k + 10% Bonus | Progress to Solutions Architect

Microsoft Fabric Consultant | DataOps | £75k + 10% Bonus | Progress to Solutions Architect

Director of Data Science

Senior MLOPS

Enterprise Data Architect | £100,000 - £120,000 | London, Hybrid


As an Enterprise Data Architect, you will define and implement data strategies, ensuring seamless data flow, governance, and scalability. You will work closely with cross-functional teams to design data architectures that meet the demanding needs of the financial sector, with a strong focus on MongoDB and Kafka for high-volume data processing.


Your expertise in finance will be crucial in ensuring compliance, optimising data pipelines, and supporting critical business decisions.


Key Responsibilities

  • Design and implement scalable, high-performance enterprise data architectures within financial services
  • Develop and optimise MongoDB implementations for structured and semi-structured data storage
  • Architect and maintain Kafka-based real-time data streaming solutions for low-latency processing
  • Define and enforce data governance, security, and compliance best practices in alignment with financial regulations.
  • Collaborate with engineering, data science, and business teams to ensure efficient data integration and accessibility
  • Evaluate and recommend emerging technologies to enhance data processing capabilities
  • Lead architectural reviews, ensuring alignment with industry best practices and business objectives
  • Provide technical leadership, mentoring teams on data modelling, database optimisation, and event-driven architectures


Skills & Experience Required

  • Extensive experience in enterprise data architecture within the financial services industry
  • Strong expertise in MongoDB, including schema design, performance tuning, and indexing strategies
  • Hands-on experience with Kafka for real-time event-driven architectures
  • Deep understanding of data governance, security, and compliance in regulated environments
  • Strong proficiency in cloud-based architectures (AWS, GCP, or Azure)
  • Experience in designing scalable, distributed, and high-availability data solutions
  • Ability to communicate complex technical concepts to non-technical stakeholders
  • Experience with data lake and warehouse architectures
  • Familiarity with NoSQL and relational databases beyond MongoDB

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.

Jobs

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

Jobs

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Jobs

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.