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

Nominate & Attend

Data Integration Engineer

PIC
London
6 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Data Engineering Lead

Data Engineer SAP {Defence, MoD

AWS Data Engineer

Data Engineer

Data Engineer

The key purpose of the role is to engineer solutions in a product centric team aligned to a business product owner.  The team contributes to the overall success of the organisation by implementing and maintaining robust technical solutions for the business. IT Development have a specific purpose in creating bespoke solutions that add value to give PIC an edge over competitors.

Requirements

Key responsibilities

  • Take a lead role in refining requirements, agreeing on solution designs, estimating effort, managing tasks effectively for integrating between Enterprise Data Management (EDM) System and Asset Valuation System and other models.
  • Implement internal applications and web services in accordance with change management policies.
  • Perform code quality, security, and testing reviews to ensure the high quality and security of computer systems and data.
  • Manage application performance requirements, tech debt, and innovate as part of continual improvement.
  • Monitor and maintain systems in line with the standard incident management process to meet business support requirements.

Knowledge, experience, skills, and abilities (technical competencies)

Technical

  • Proficiency in one or more structured programming languages such as C# and Python.
  • Good experience with version control systems like Git.
  • Deep understanding of data structures, algorithms, and system design and data virtualisation
  • Proficiency with data storage solutions including Cloud, File Storage and SQL databases
  • Experience with testing frameworks and methodologies.
  • Strong design and implementation skills of enterprise applications with cloud-based architecture, APIs, containerization and microservices.
  • Proficiency with CI/CD pipelines and DevOps practices.
  • Experience of cybersecurity principles and practices.

Desirable:

  • Expertise in cloud platforms like Azure, AWS or Google Cloud.
  • Knowledge of containerization technologies like Docker and orchestration tools like Kubernetes.
  • Experience of fixed income products (bonds and swaps).

Benefits

  • 28 days’ annual leave plus bank holidays
  • Pension
  • Insurance for Travel, Private Medical, Critical Illness, Life Assurance and Income Protection
  • Save As You Earn (SAYE)

And more

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.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.

Top 10 Mistakes Candidates Make When Applying for Machine-Learning Jobs—And How to Avoid Them

Landing a machine-learning job in the UK is competitive. Learn the 10 biggest mistakes applicants make—plus tested fixes, expert resources and live links that will help you secure your next ML role. Introduction From fintechs in London’s Square Mile to advanced-research hubs in Cambridge, demand for machine-learning talent is exploding. Job boards such as MachineLearningJobs.co.uk list new vacancies daily, and LinkedIn shows more than 10,000 open ML roles across the UK right now. Yet hiring managers still reject most CVs long before interview—often for avoidable errors. Below are the ten most common mistakes we see, each paired with a practical fix and a live resource link so you can dive deeper.