Software Engineering Manager - Data Platform

Cathcart Technology
Edinburgh
1 month ago
Applications closed

Related Jobs

View all jobs

Software Engineering Manager

Software Engineering Manager

TechOps Engineering Manager

Gen AI Engineering Manager, Human Data Quality

Data Engineering Manager

Data Engineering Manager

Software Engineering Manager with a Data Platform focus, required for a globally known software business, based from Edinburgh. You will be working on developing world-class products and services in a hugely innovative environment.The company:The business has been going for nearly 20 years and have over 1,000 staff. They operate across a very specific area of online sales and are focused on travel. They have offices in London and Scotland, and are continuing to grow and be productive, even in a tough market at the moment.They are one of Scotland's best known tech organisations, and they thrive on a positive and welcoming culture, making it one of the best places to work. They are a hybrid organisation and ask all employees to be in office twice a week in Edinburgh - what days those are, are flexible.The role:You will be managing a predominantly Agile and fairly large team of 11 Engineers (including you), of mainly Software Engineers and two Data Engineers, of varying levels. The team are currently without a Manager, due to some internal promotions, and they need someone to help steer the ship. They are looking for people from a strong and innovative Data Engineering background and experience of managing small and Agile teams. It would be great too if you have an understanding of Data Architecture as well as an input into systems design. The key however really is on the development of the team and making sure they grow and develop as individuals.This role is focused on developing a Data Platform and Platform skills in general would be highly advantageous.The tech stack for the team is quite niche, but they generally use a combination of Python, Java, AWS and niche data pipeline tooling , and it is likely that you will come from this background and have managed teams in this stack. Although it is a management position, the ability to still look at Code Reviews and be a little hands-on and technical would be beneficial.Package & Office/Location:You can expect all the perks of a modern software company, including: a stunning custom-built office in the city centre, breakout rooms, pool tables, regular social events, top of the range kit and a very flexible approach to working hours and indeed, work life balance.The package on offer is very strong overall, with great benefits. We are able to offer a base salary in the region of £70-80k depending on your experience/skills, as well as a few different bonus' per year and other flexible benefits.This is an opportunity to work for one of Scotland's best tech employers and if you are a Data Engineering Manager / Team Lead keen to make your mark in a world leading company, get in touch with Hamish at Cathcart Technology for a more detailed conversation.TPBN1_UKTJ

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.

Data Science Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Data science has become a linchpin in modern business, transforming oceans of raw data into actionable insights that guide strategy, product development, and personalised customer experiences. With this surge in data-centric operations, the need for effective data science leadership has never been more critical. Guiding a team of data scientists, analysts, and machine learning engineers requires not only technical acumen but also the ability to foster collaboration, champion ethical practices, and align complex modelling efforts with overarching business goals. This article provides practical guidance for managers and aspiring leaders aiming to excel in data-driven environments. By exploring strategies to motivate data science professionals, develop mentoring frameworks, and set achievable milestones, you will be better prepared to steer your team towards meaningful, evidence-based outcomes.