Data Engineering Manager

Cathcart Technology
Edinburgh
3 days ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Lead a high-performing data engineering team in Edinburgh, driving the development of large-scale, reliable data systems that enable analytics, insight, and operational decision-making across a fast-paced technology organisation.


The Opportunity

You’ll oversee a team of skilled data engineers, guiding the design and delivery of scalable data pipelines and platforms that handle massive datasets. You’ll help your team solve complex engineering challenges while maintaining high standards of data quality, reliability, and operational excellence.


We’re looking for someone with a strong technical background who can provide strategic oversight, direct architectural discussions, review implementations, and ensure engineering best practices are applied, while mentoring and coaching your team to grow their skills and take ownership of delivery. You’ll have previous hands-on experience with Java or Python, cloud platforms (AWS, GCP, or Azure), whilst working closely with cross functional teams to translate analytics and business needs into practical, high-impact data solutions.


The Company

This Edinburgh-based technology company is recognised globally for its innovative, data-driven approach. They foster a collaborative, forward-thinking culture where engineers work on large-scale datasets, distributed systems, and modern cloud platforms. Teams leverage cutting-edge tools such as Spark, Airflow, Kafka, dbt, and Databricks to build resilient, scalable, and high-quality data solutions.


Why this role?

** Lead a talented team of data engineers delivering high-quality, reliable data systems.

** Shape the architecture and delivery of data pipelines, platforms, and products from design through production.

** Promote a culture of autonomy, learning, and continuous improvement within your team.

** Collaborate across teams and stakeholders to translate business priorities into actionable technical solutions.

** Work with modern data technologies and massive datasets to tackle challenging engineering problems.


Who you are:

** An experienced Data Engineering manager who has previously worked hands on in building and maintaining data pipelines or platforms.

** Proven experience managing or mentoring data engineers, providing support and guidance to help teams thrive.

** Comfortable operating in complex environments, delivering high-quality solutions under tight deadlines.

** Passionate about data engineering, modern tooling, and applying best practices to solve challenging technical problems.

** An effective communicator and collaborator, able to bridge technical and business priorities.


The Offer:

You’ll receive a competitive salary, bonus opportunity, and a great benefits package too. Hybrid working is available, with two days per week onsite in a modern Edinburgh city centre office.


This is a unique chance to lead a talented data engineering team, build world-class data systems, and shape the careers of engineers in a high-impact, high-growth technology environment.


If this sounds exciting, please apply or reach out to Murray Simpson.

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.

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.