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

Nominate & Attend

Full Stack Data Engineer

JR United Kingdom
London
4 days ago
Create job alert

Social network you want to login/join with:
Location: London – Mostly remote initially
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

#J-18808-Ljbffr

Related Jobs

View all jobs

Full Stack Data Engineer

Full Stack Data Engineer

Full Stack / Data Engineer

Full Stack / Data Engineer

Senior Full Stack Data Engineer

Senior Machine Learning 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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.