Data Engineer

Nine Twenty
Glasgow
1 month ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

An established technology consultancy is looking to hire an experienced Data Engineer to work on large-scale, customer-facing data projects while also contributing to the development of internal data services. This role blends hands‑on engineering with architecture design and technical advisory work, offering exposure to enterprise clients and modern cloud platforms.


You will play a key role in designing and delivering cloud-native data platforms, working closely with engineering teams, stakeholders, and customers from initial design through to production release. The role offers variety, autonomy, and the opportunity to work with leading‑edge data technologies across Azure and AWS.


The role

As a Data Engineer, you will be responsible for designing, building, and maintaining scalable data platforms and pipelines. You will support and lead technical workshops, contribute to architecture decisions, and act as a trusted technical partner on complex data initiatives.


Key responsibilities include:



  • Designing and building scalable data platforms and ETL/ELT pipelines in Azure and AWS
  • Implementing serverless, batch, and streaming data architectures
  • Working hands‑on with Spark, Python, Databricks, and SQL‑based analytics platforms
  • Designing Lakehouse‑style architectures and analytical data models
  • Feeding behavioural and analytical data back into production systemsSupporting architecture reviews, design sessions, and technical workshops
  • Collaborating with engineering, analytics, and commercial teams
  • Advising customers throughout the full project lifecycle
  • Contributing to internal data services, standards, and best practices

What we are looking for

Essential experience



  • Proven experience as a Data Engineer working with large‑scale data platforms
  • Strong hands‑on experience in either Azure or AWS, with working knowledge of the other
  • Azure experience with Lakehouse concepts, Data Factory, Synapse and/or Fabric
  • AWS experience with Redshift, Lambda, and SQL‑based analytics services
  • Strong Python skills and experience using Apache Spark
  • Hands‑on experience with Databricks
  • Experience designing and maintaining ETL/ELT pipelines
  • Solid understanding of data modelling techniques
  • Experience working in cross‑functional teams on cloud‑based data platforms
  • Ability to work with SDKs and APIs across cloud services
  • Strong communication skills and a customer‑focused approach

Desirable experience

  • Data migrations and platform modernization projects
  • Implementing machine learning models using Python
  • Consulting or customer‑facing engineering roles
  • Feeding analytics insights back into operational systems

Certifications (beneficial but not required)

  • AWS Solutions Architect Associate
  • Azure Solutions Architect Associate
  • AWS Data Engineer Associate
  • Azure Data Engineer Associate

What s on offer

  • The opportunity to work on modern cloud and data projects using leading technologies
  • A collaborative engineering culture with highly skilled colleagues
  • Structured learning paths and access to training and certifications
  • Certification exam fees covered and certification‑related bonuses
  • Competitive salary and comprehensive benefits package
  • A supportive and inclusive working environment with regular knowledge sharing and team events

This role would suit a Data Engineer who enjoys combining deep technical work with customer interaction and wants to continue developing their expertise across cloud and data platforms. If you would like to find out more, then please get in contact with Jack at (url removed).


#J-18808-Ljbffr

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.