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

Apply Now

Lead Data Architect

Xcede
London
9 months ago
Applications closed

Related Jobs

View all jobs

Lead Data & Machine Learning Architect

Lead Data & Machine Learning Architect

Lead Data & Machine Learning Architect

Lead Data & Machine Learning Architect

Lead Data Engineer

Lead Data Engineer

Lead Data Architect

London office x3 days per week

Up to £130,000 Salary


OVERVIEW

As the Lead Data Architect, you will be responsible for designing and implementing the overall data architecture strategy for our organization. This role requires a deep understanding of data modeling, cloud platforms, and big data technologies, combined with a strategic mindset to support our business goals in the rapidly evolving financial services industry.

YOUR RESPONSIBILITIES:

The Data Architect's responsibilities will include, but not be limited to:

  • Lead the design and implementation of scalable, secure, and high-performance data architectures for both structured and unstructured data.
  • Work with business stakeholders and technical teams to understand data needs and translate them into actionable data solutions.
  • Develop and maintain best practices for data modeling, ETL processes, data governance, and data quality.
  • Lead the migration of legacy systems to modern cloud-based platforms (e.g., AWS, Azure, Google Cloud).
  • Define and enforce data security standards and protocols to ensure compliance with financial industry regulations.
  • Oversee the development of data pipelines, data lakes, and data warehouses, ensuring they are optimized for real-time and batch processing.
  • Mentor and guide junior architects and engineers, fostering a culture of innovation and continuous learning.
  • Stay up-to-date with emerging data technologies and trends, recommending new tools and techniques to enhance the company’s data capabilities.

YOUR SKILLS & EXPERIENCE

A successful Data Architect will have the following:

  • Extensive experience with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (Hadoop, Spark, Kafka, etc.).
  • Strong expertise in data modeling, ETL processes, data warehousing, and data governance.
  • In-depth knowledge of financial services regulations and compliance requirements (e.g., GDPR, PCI-DSS, SOX).
  • Proven experience designing and implementing end-to-end data solutions, including data lakes, data warehouses, and real-time data streaming architectures.

HOW TO APPLY

Please register your interest by sending your CV to for more info!

This role does not offer sponsorship!

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.