At a Glance
- Tasks: Build and maintain data processing pipelines for satellite and Earth Observation data.
- Company: Join a forward-thinking company at the forefront of Earth Observation technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and continuous improvement.
- Why this job: Make a real impact by transforming raw data into valuable insights for global customers.
- Qualifications: Strong Python skills, Linux experience, and knowledge of data processing concepts required.
The predicted salary is between 45000 - 55000 € per year.
Requirements
- Strong Python capability for building data processing pipelines
- Confidence working in Linux environments to run and maintain workflows
- Solid understanding of data ingestion, transformation and processing pipelines
- Ability to design and manage data structures, formats and metadata standards
- Capability to work with APIs and databases (particularly REST interfaces and PostgreSQL)
- Understanding of data-driven and event-driven architectures
- Knowledge of satellite imagery and Earth Observation data processing concepts
- Familiarity with geospatial tools such as QGIS, ArcGIS or similar
- Awareness of containerised and orchestrated environments (e.g. Kubernetes)
- Ability to translate analytical or scientific code into efficient, production-ready systems
What the job involves
- As a Data Engineer, you’ll be at the core of how we turn raw Earth Observation data into scalable, reliable and high-quality data products.
- You’ll design and build the pipelines and systems that power our data platform, ensuring customers across the world can access and act on satellite data with confidence.
- Developing and maintaining data ingestion and processing pipelines for satellite and Earth Observation data.
- Designing and implementing scalable, reliable processing systems to support payload data processing and quality control.
- Establishing and enforcing data and metadata standards to ensure consistency, usability and quality across datasets.
- Balancing customer needs with technical architecture, delivering solutions aligned with platform and operational constraints.
- Proposing and implementing improvements to data architecture, scalability and performance.
- Integrating new data processing techniques and data types into existing workflows.
- Translating scientific or analytical code into efficient, production-ready implementations.
- Maintaining and evolving complex data processing systems with monitoring, reliability and continuous improvement in mind.
- Supporting EO data quality and performance through validation, control and optimisation mechanisms.
Data Software Engineer in Oxford employer: Deepstreamtech
As a Data Software Engineer, you will join a forward-thinking company that prioritises innovation and collaboration in the heart of a vibrant tech community. With a strong emphasis on employee growth, we offer extensive training opportunities and a supportive work culture that values creativity and teamwork. Our commitment to sustainability and cutting-edge technology ensures that you will be part of meaningful projects that make a real impact on global data accessibility.
StudySmarter Expert Advice🤫
We think this is how you could land Data Software Engineer in Oxford
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the industry. Attend meetups, webinars, or even just grab a coffee with someone who’s already in the field. You never know when a casual chat might lead to your next big opportunity.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving data processing pipelines or geospatial tools. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and database skills. Practice coding challenges and be ready to discuss your experience with APIs and data architectures. Confidence is key, so make sure you can talk through your thought process!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us. Tailor your application to highlight your experience with Earth Observation data and how you can contribute to our mission.
We think you need these skills to ace Data Software Engineer in Oxford
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your strong Python capabilities in your application. We want to see how you've built data processing pipelines before, so share specific examples that showcase your experience!
Get Comfortable with Linux:Since you'll be working in Linux environments, it's a good idea to mention any relevant experience you have. Talk about how you've run and maintained workflows in Linux, as this will show us you're ready for the role.
Demonstrate Your Data Knowledge:We love seeing candidates who understand data ingestion, transformation, and processing pipelines. Make sure to explain your familiarity with these concepts and any tools you've used, especially if you've worked with APIs or databases like PostgreSQL.
Tailor Your Application:Take the time to tailor your application to our job description. Highlight your experience with satellite imagery, geospatial tools, and containerised environments. This will help us see how you fit into our team and the exciting work we do!
How to prepare for a job interview at Deepstreamtech
✨Show Off Your Python Skills
Make sure to brush up on your Python capabilities, especially in building data processing pipelines. Be ready to discuss specific projects where you've used Python to solve problems or improve processes.
✨Get Comfortable with Linux
Since you'll be working in Linux environments, it’s crucial to demonstrate your confidence here. Familiarise yourself with common commands and workflows, and be prepared to explain how you've maintained workflows in previous roles.
✨Understand Data Pipelines Inside Out
Be ready to talk about your experience with data ingestion, transformation, and processing pipelines. Think of examples where you designed or managed data structures and how you ensured data quality and usability.
✨Familiarity with Geospatial Tools is Key
If you have experience with tools like QGIS or ArcGIS, make sure to highlight that. Discuss any projects where you’ve worked with satellite imagery or Earth Observation data, as this will show your relevance to the role.
