National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Enterprise Data Architect

developrec
London
4 months ago
Applications closed

Related Jobs

View all jobs

Enterprise Data Architect

Enterprise Data Architect

Data Governance Architect

Principle Data Engineer ( AWS & Airflow )

Data Science Manager - Marketing & Customer Generative AI Enterprise Architect

Lead Data Engineer

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
National AI Awards 2025

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 Get a Better AI Job After a Lay-Off or Redundancy

Being made redundant or laid off can feel like the rug has been pulled from under you. Whether part of a wider company restructuring, budget cuts, or market shifts in tech, many skilled professionals in the AI industry have recently found themselves unexpectedly jobless. But while redundancy brings immediate financial and emotional stress, it can also be a powerful catalyst for career growth. In the fast-evolving field of artificial intelligence, where new roles and specialisms emerge constantly, bouncing back stronger is not only possible—it’s likely. In this guide, we’ll walk you through a step-by-step action plan for turning redundancy into your next big opportunity. From managing the shock to targeting better AI jobs, updating your CV, and approaching recruiters the smart way, we’ll help you move from setback to comeback.

AI Jobs Salary Calculator 2025: Work Out Your Market Value in Seconds

Why your 2024 salary data is already outdated “Am I being paid what I’m worth?” It is the question that creeps in whenever you update your CV, see a former colleague announce a punchy pay rise on LinkedIn, or notice a recruiter slide into your inbox with a role that looks eerily similar to your current one—only advertised at £20k more. Artificial intelligence moves faster than any other hiring market. New frameworks are open‑sourced overnight, venture capital floods specific niches without warning, & entire job titles—Prompt Engineer, LLM Ops Specialist—appear in the time it takes most industries to schedule a meeting. In that environment, salary guides published only a year ago already look like historical curiosities. To give AI professionals an up‑to‑the‑minute benchmark, ArtificialIntelligenceJobs.co.uk has built a simple yet powerful salary‑calculation formula. By combining three variables—role, UK region, & seniority—you can estimate a realistic 2025 salary band in less than a minute. This article explains that formula, unpacks the latest trends driving pay, & offers concrete steps to boost your personal market value over the next 90 days.

How to Present AI Models to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

In today’s competitive job market, AI professionals are expected to do more than just build brilliant algorithms—they must also explain them clearly to stakeholders who may have no technical background. Whether you're applying for a role as a machine learning engineer, data scientist, or AI consultant, your ability to articulate complex models in simple terms is fast becoming one of the most valued soft skills in interviews and on the job. This guide will help you master the art of public speaking for AI roles, offering tips on structuring presentations, designing effective slides, and using storytelling to make your work resonate with any audience.