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

Nominate & Attend

Full Stack Data Engineer (City of London)

Kolayo
City of London
5 days ago
Create job alert

Location: London – Mostly remote initially

Salary: £35k - £50k depending on experience

Employment Type: Full-time


About Us:


At Kolayo, we're dedicated to building innovative, data-driven solutions that empower businesses and organisations to make smarter, faster decisions. We specialise in developing cutting-edge technologies and having recently secured funding to accelerate our growth. We are looking for a highly skilled Full Stack Developer with expertise primarily in database design and administration, Python and React to help us deliver exceptional, data-centric applications. Join us in making an impact while growing your career in a fast-paced and collaborative environment.


Role Overview:


We are looking for a developer with strong foundational knowledge of database design and web applications. In this role, you'll be working on a range of projects from data modelling, server administration, building the front and back end of web apps and working with clients to integrate their systems into our analytical model. You will also need to be adaptable and love learning new technologies as we on-board clients with a range of technologies you may have never seen before, whilst taking care to ensure client data is secure and protected at all times. As part of our growing team, you'll be closely collaborating with the founders to develop our systems and processes from the ground up.


Key Responsibilities:


  • Design, develop, and maintain efficient, fast and scalable databases for real-time analytics.
  • Write and optimize SQL for data retrieval, reporting, and transformation.
  • Build and maintain full-stack web applications using Python and React.
  • Develop Python scripts and services to handle data processing and ETL tasks.
  • Collaborate with co-founders to define database schema and data pipelines, ensuring seamless integration with our applications.
  • Always be conscious of security and performance considerations, to keep client confidence high and service costs low.
  • Develop reusable integrations with existing client systems and APIs.


Required Skills & Experience:


  • Experience as a Full Stack Developer with a focus on databases and front/back end technologies
  • Extensive experience with relational databases (Postgres, MySQL, etc), including query optimization, schema design, and data modelling.
  • Proficiency with Python for backend services, data processing, and integration tasks.
  • Experience with a modern front-end technology like React or Vue.js.
  • Experience using, designing and documenting APIs and associated authentication methods.
  • Familiarity with version control systems, ideally Git.
  • Strong analytical and troubleshooting skills, with the ability to resolve complex data-related issues.


Nice to Have:


  • Familiarity with cloud platforms (AWS, GCP, Azure) and cloud-based database services (Snowflake).
  • Knowledge of data warehousing, orchestration and pipeline technologies (Apache Airflow/Kafka, Azure DataFactory etc.).
  • Experience with DBT for modelling
  • Server administration and networking fundamentals


Related Jobs

View all jobs

Senior Full Stack Developer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

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.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

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.