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- Tasks: Design and maintain pipelines for large-scale geospatial data analysis.
- Company: Join a leading firm in digital transformation and geospatial solutions.
- Benefits: Enjoy remote work, competitive pay, and a flexible contract.
- Why this job: Be part of innovative projects that shape the future of geospatial technology.
- Qualifications: Strong Python skills and experience with cloud platforms and spatial databases required.
- Other info: Candidates must pass BPSS security checks.
The predicted salary is between 36000 - 60000 £ per year.
Hit Apply below to send your application for consideration. Ensure that your CV is up to date, and that you have read the job specs first.
- 6 month contract (initially)
- Remote-Working
- Outside IR35
- Market Rates
The Opportunity: ISR are proud to be supporting a high-profile digital transformation programme and we’re looking for an experienced Geospatial Data Engineer to join the team on a contract basis. In this role, you'll work at the intersection of geospatial data and cloud engineering – designing, building and maintaining robust pipelines that enable the transformation and analysis of large-scale geospatial datasets.
Skills and Experience:
- Strong programming skills in Python, with experience using libraries such as GeoPandas, Shapely and GDAL
- Experience with cloud platforms (AWS, Azure or GCP) and infrastructure-as-code tools
- Proficiency in spatial databases (e.g., PostGIS) and data pipeline tools (e.g., Airflow)
- Familiarity with geospatial APIs, formats (GeoJSON, WKT) and data services
Security Clearance: Candidates must be eligible to pass Baseline Personnel Security Standard (BPSS) checks.
Geospatial Data Engineer employer: ISR RECRUITMENT LIMITED
Contact Detail:
ISR RECRUITMENT LIMITED Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Geospatial Data Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in geospatial data engineering. Follow industry leaders on social media and engage in relevant online communities to stay updated on best practices and emerging technologies.
✨Tip Number 2
Network with professionals in the geospatial field. Attend webinars, workshops, or local meetups to connect with others who work in similar roles. This can lead to valuable insights and potential referrals.
✨Tip Number 3
Showcase your technical skills through personal projects or contributions to open-source initiatives. Having a portfolio that demonstrates your proficiency in Python, cloud platforms, and spatial databases can set you apart from other candidates.
✨Tip Number 4
Prepare for technical interviews by practising coding challenges related to geospatial data processing. Familiarise yourself with common algorithms and data structures used in this field to boost your confidence during the interview.
We think you need these skills to ace Geospatial Data Engineer
Some tips for your application 🫡
Understand the Job Requirements: Carefully read the job description for the Geospatial Data Engineer position. Make sure you understand the skills and experience required, such as programming in Python and familiarity with cloud platforms.
Tailor Your CV: Update your CV to highlight relevant experience and skills that match the job specifications. Emphasise your programming skills, experience with geospatial data, and any relevant projects you've worked on.
Craft a Compelling Cover Letter: Write a cover letter that explains why you're a great fit for the role. Mention specific experiences that demonstrate your expertise in geospatial data engineering and how you can contribute to the company's digital transformation programme.
Double-Check Your Application: Before submitting, review your application for any errors or missing information. Ensure that all documents are correctly formatted and that your contact details are up to date.
How to prepare for a job interview at ISR RECRUITMENT LIMITED
✨Showcase Your Technical Skills
Make sure to highlight your programming skills in Python, especially with libraries like GeoPandas, Shapely, and GDAL. Be prepared to discuss specific projects where you've used these tools to solve real-world problems.
✨Demonstrate Cloud Experience
Since the role involves cloud engineering, be ready to talk about your experience with platforms like AWS, Azure, or GCP. Mention any infrastructure-as-code tools you've used and how they contributed to your projects.
✨Discuss Spatial Databases
Familiarise yourself with spatial databases such as PostGIS. Be prepared to explain how you've used them in past roles, particularly in relation to data pipelines and analysis of geospatial datasets.
✨Understand Geospatial APIs and Formats
Brush up on your knowledge of geospatial APIs and formats like GeoJSON and WKT. Being able to discuss how you've worked with these in previous projects will demonstrate your expertise in the field.
