Senior Backend Engineer

LiveEO; Berlin; On-site; EUR 90,000 - 120,000; Full time

Job summary

LiveEO is seeking a strong generalist software engineer to enhance core backend services and data pipelines in Python, deployed on Kubernetes in a Berlin office setting.

You will focus on performance, observability, and scalability of end-to-end processing pipelines, while maintaining stable interfaces and reliable releases. Collaboration across product, data, devops and geospatial teams is essential.

Qualifications

• 5+ years of experience building and operating production backend services or data pipelines in Python.
• Solid track record maintaining and scaling services in production: performance, observability, testing, incident handling.
• Hands-on experience deploying and operating services on Kubernetes, including troubleshooting and incident response.
• Strong relational database skills; comfortable with API design and service-to-service contracts.
• Experience working across multiple teams on shared interfaces or contracts.
• Raster processing or satellite imagery background.
• Geospatial data experience (PostGIS or similar).
• Experience running workloads on AWS.
• Experience with a workflow orchestrator (Prefect, Airflow or similar).
• You’ve used AI-assisted coding in your day-to-day, not just tried it once.

Responsibilities

• Own the maintenance, performance and scalability of core backend services, evolving data models, APIs and storage.
• Maintain a clear, shared view of the health of the end-to-end product pipeline and detect regressions early.
• Build and uphold monitoring, alerting, automated quality checks and testing across services.
• Help keep interfaces between services stable; spot schema drift and contract failures.
• Contribute to safer release practices: backwards compatibility, feature flags and staged rollouts.
• Maintain and improve workflow orchestration and automation around it; reduce manual steps.
• Turn observed system behaviour into concrete improvement work and feed results to planning.
• Mentor engineers through code review and pairing; raise the bar on scoping, testing and release stability.

Skills

Python

Kubernetes

AWS

PostGIS

Satellite imagery

Observability

Code review

Airflow

Tools

Prefect

Airflow

Job description

• You will work on applications that use deep learning and satellite data and other data sources to help companies and governments fight deforestation, monitor critical infrastructure, and respond faster and more precisely to natural disasters
• Our aim is to empower any user in the world to harness the power of earth observation satellites to simplify and improve their daily work
• You will join the team that turns analytics outputs into data products and makes them available across the platform and to customers. We already have deep geospatial and data engineering expertise in the team; what we need is a strong generalist software engineer who makes our core services and pipelines more reliable, observable and scalable
• Concrete topics you would work on are, for example, the performance and scalability of backend services serving large volumes of geospatial data, the health and observability of our end-to-end processing pipeline, and the stability of the interfaces between the services that make it up
• We are a team of five engineers and three geospatial analysts today, embedded in a cross‑functional group of product managers, UX/UI designers, data, devops, ML, and geospatial engineering experts. You will not be the only person responsible for any system you touch, but you will play a crucial role in how we evolve our services and components
• Own the maintenance, performance and scalability of core backend services, evolving their data models, APIs and storage as data volumes and consumers grow
• Maintain a clear, shared view of the health of the end-to‑end product pipeline so that regressions and failures are detected early rather than discovered late or through manual coordination
• Build and uphold the practices that make this possible: monitoring, alerting, automated quality checks and testing across services
• Help keep the interfaces between services stable: spot schema drift, contract failures and version incompatibilities early, feed concrete failure cases back to the owning engineers and help establish durable contracts
• Contribute to safer release practices such as backwards compatibility, feature flags and staged rollouts
• Maintain and improve our workflow orchestration and the automation around it, reducing manual steps and operational toil
• Turn observed system behaviour into concrete improvement work and bring it into team planning
• Mentor engineers through code review and pairing; raise the bar on scoping, testing and release stability

• At least 5 years of experience building and operating production backend services or data pipelines in Python
• Solid track record maintaining and scaling services already in production: performance work, observability, testing, incident handling
• You’ve used AI-assisted coding in your actual day‑to‑day, not just tried it once
• Hands‑on experience deploying and operating services on Kubernetes, including troubleshooting and incident response
• Strong relational database skills; comfortable with API design and service‑to‑service contracts
• Experience working across multiple teams on shared interfaces or contracts
• Spec‑driven or test‑driven development, agentic or otherwise
• You do not need all of the “nice to haves,” and you do not need to match every “must have” perfectly. If you read this and think you’d be a good fit but you’re missing a line item, apply and tell us what you’d bring instead
• Raster processing or satellite imagery background
• Geospatial data experience (PostGIS or similar)
• Experience running workloads on AWS
• Experience with a workflow orchestrator (Prefect, Airflow or similar)