Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Geospatial Data Engineer | Outside IR35 | Remote

London
4 days ago
Create job alert

Geospatial Data Engineer | Outside IR35 | Remote
FME Workflows | Geoprocessing | Grid/Hex Modelling | Renewable Energy | ETL

SR2 is working with a leading consultancy and currently looking for a Geospatial Data Engineer to work to work on energy and modelling project. 

You’ll play a key role in re-engineering existing ArcGIS Pro and FME workflows, helping transition from vector-based processing to a grid/hexagonal data model to improve scalability and analytical flexibility. This is a hands-on role for an experienced FME specialist who can quickly add value, working alongside engineers while also advising on optimisation and best practice.

Key Responsibilities:

Design, build, and optimise FME workbenches to support migration from vector overlays to grid/hex-based models
Collaborate with GIS and engineering teams to translate requirements into scalable workflows
Implement data transformation, validation, and automation to improve model accuracy and performance
Optimise and restructure legacy FME workbenches for maintainability
Support integration with ArcGIS Pro and downstream analytical workflows
Provide knowledge transfer, documentation, and mentoring to in-house staffSkills/Experience

Strong track record delivering production FME workflows in complex environments
Deep knowledge of geoprocessing methods and spatial data structures (vector, raster, grid/hex)
Experience integrating FME with ArcGIS Pro and Esri ecosystems
Familiarity with suitability modelling or spatial multi-criteria analysis (SMCA) desirable
Skilled in ETL processes, spatial data management, and performance optimisation
Strong stakeholder and team collaboration skillsDesirable Experience:

Renewable energy, environmental, or land suitability assessments
Python scripting in FME for automation/custom transformers
Experience handling large-scale geospatial datasets
Agile delivery environmentsThe Details

Duration: 3 months intially
Location: Remote
Outside IR35
Start: ASAPIf you’re an FME specialist with a passion for geospatial data engineering and want to work on cutting-edge suitability modelling in the renewable energy sector — apply now for immediate consideration.
Call Settings Override From Record Yes No Always use these settings

Related Jobs

View all jobs

Principal Geospatial Data Engineer

Data Engineer, Geospatial

Senior Data Engineer

Lead Data Engineer

Data Engineer (Remote)

Data Engineer – Talent Pipeline

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.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.

Top 10 Skills in Machine Learning According to LinkedIn & Indeed Job Postings

Machine learning (ML) is at the forefront of innovation, powering systems in finance, healthcare, retail, logistics, and beyond in the UK. As organisations leverage ML for predictive analytics, automation, and intelligent systems, demand for skilled practitioners continues to grow. So, which skills are most in demand? Drawing on insights from LinkedIn and Indeed, this article outlines the Top 10 machine learning skills UK employers are looking for in 2025. You'll learn how to demonstrate these capabilities through your CV, interviews, and real-world projects.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has become one of the most powerful forces reshaping the modern world. From voice assistants and recommendation engines to fraud detection and medical imaging, it underpins countless applications. ML is no longer confined to research labs—it powers business models, public services, and consumer technologies across the globe. In the UK, demand for machine learning professionals has risen dramatically. Organisations in finance, retail, healthcare, and defence are embedding ML into their operations. Start-ups in Cambridge, London, and Edinburgh are pioneering innovations, while government-backed initiatives aim to position the UK as a global AI leader. Salaries for ML engineers and researchers are among the highest in the tech sector. Yet despite its current importance, machine learning is only at the beginning of its journey. Advances in generative AI, quantum computing, robotics, and ethical governance will reshape the profession. Many of the most vital machine learning jobs of the next two decades don’t exist today. This article explores why new careers will emerge, the roles likely to appear, how today’s roles will evolve, why the UK is well positioned, and how professionals can prepare now.