National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Geospatial Data Engineer

Omnis Partners
Newcastle upon Tyne
2 months ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer with Data Engineering expertise

Senior Geospatial Data Scientist

Senior Data Scientist

Senior Data Scientist

Data Scientist

Data Analyst

Associate Director of Geospatial Data Engineering | £140k | Remote (UK) | Open Source + Geospatial + AI-adjacent 📣


We’re working with a forward-thinking data consultancy that’s looking for ahands-on Associate Director of Geospatial Data Engineering— someone who blends deep technical ability with creativity, and loves solving unusual data challenges with open-source tools.

This is a unique opportunity to take ownership of strategic data engineering projects — helping clients build modern, scalable data platforms while leading from the front with your own engineering expertise.


🔧 What you'll be working with:

  • Python-first data engineering, building custom pipelines, automation tools and ingestion workflows.
  • PostgreSQL + PostGIS: serious spatial querying, indexing and geospatial wrangling.
  • Cloud-native infrastructure: AWS / GCP / Azure (your pick) — but with a proper understanding of how it all works under the hood.
  • Modern ETL/ELTusing Airflow, Spark, Dagster, Prefect — you choose the right tool for the job.
  • CI/CD for data: Git, Docker, automated testing, efficient and scalable workflows.


🗺️ What sets this role apart:

  • Heavy emphasis ongeospatial data engineering— working with OSM, map tile rendering, Leaflet.js, Kepler.gl, and data visualisation.
  • Work on projects blendingprivate + public + non-traditional data sources— edge devices, IoT, NLP pipelines, and custom data processing challenges.
  • Preference for open-source tools (QGIS, SpaCy, MapTiler etc.) over proprietary systems.
  • A chance to shape the strategy, lead delivery, and stay close to the tech.


🧠 You might be a fit if you:

  • Have a deep understanding of systems, efficiency, and optimisation (e.g., edge computing, AI-on-device, or automation with Raspberry Pi).
  • Are a natural problem-solver who can connect data points others miss.
  • Enjoy tackling messy, unconventional datasets.
  • Have a track record ofpersonal projects, open-source contributions or building beyond the 9–5
National AI Awards 2025

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.

Jobs

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Education

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

Careers

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.