Full Stack Data Engineer

Kolayo
London
9 months ago
Applications closed

Related Jobs

View all jobs

Full Stack Data Engineer (Client Facing)

Full Stack Data Engineer (Client Facing)

Senior Full Stack Data Engineer (Client Facing)

Senior Full Stack Data Engineer (Client Facing)

Senior Full-Stack Data Engineer (Python/Java)

Data Scientist - Supply Chain Optimisation

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


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 Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.