Data Engineer - London

London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer - Join One of the UK's Most Exciting Tech Start-ups

Location: London (Hybrid)

Salary: £40,000-£65,000 + Equity

Our client, one of the UK's fastest-growing and most exciting tech start-ups, is looking for a talented Data Engineer to help shape the future of its data strategy. Named one of LinkedIn's Top 10 UK Start-ups and now operating Nation-wide, this is a unique opportunity to join a high-growth business that's already making a meaningful impact and has lots more to come!

The Role:

As a Data Engineer, you'll design, build and maintain scalable data pipelines and architecture that support analytics feeding directly into customer-facing mobile and web applications, as well as internal tools used to drive strategic decisions.

Key Responsibilities:

Build and maintain scalable data pipelines to support both internal dashboards and customer-facing products
Design and implement efficient data architecture for optimal storage, retrieval, and processing
Develop ETL processes to ingest, transform, and load data from various sources, particularly APIs
Collaborate with data scientists and software engineers to align data strategies with app development
Work with internal stakeholders to shape and meet business data needs
Maintain documentation, monitor pipeline performance, and resolve issues as they ariseAbout You

Strong problem-solving skills, demonstrated through academic or professional experience
In-depth understanding of data architecture, data-modelling, and best practices in data engineering
Proficient in Python and SQL; experience with data processing frameworks such as Airflow, TensorFlow, or Spark is advantageous
Willingness to gain working knowledge of backend development (e.g., Python with Django) for pipeline integration
Familiarity with data versioning, quality management, and CI/CD pipelines
Experience with cloud platforms (e.g., AWS or Azure) and data tools such as Terraform or SageMaker is a plus
Ideally, some hands-on experience building and maintaining data pipelines in a production environmentWhat's on Offer:

Competitive salary: £40,000-£65,000, dependent on skills and experience
Private medical insurance
Equity in a well-funded, high-growth start-up

Office gym membership
Dog-friendly office located in the heart of Camden
A supportive, social, and dynamic team cultureThis is an exceptional opportunity for a data engineer who wants to make an impact at scale, grow in a supportive environment, and be part of an ambitious team at the forefront of UK tech innovation.

If you're ready for your next challenge, we'd love to hear from you.

People Source Consulting Ltd is acting as an Employment Agency in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas

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 Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.