The Role
Own and evolve the platform that turns research models and data into reproducible, auditable client deliverables. Lead Python-based data infrastructure, CI/CD, pipeline orchestration, GCP architecture, infrastructure-as-code, monitoring, access management, and geospatial workflows. Review designs, establish engineering standards, mentor engineers, and coordinate infrastructure priorities. The role also involves production data systems, schema design, model versioning, containers, observability, and collaboration with software, data, science, and solutions teams.
Summary Generated by Built In
The Role:
Our growing team is looking for a senior software engineer to lead the evolution of the infrastructure that turns our science into trustworthy climate results. In this role, you'll own the platform that takes our data, models and estimation methods from R&D to auditable client deliverables, and you'll be a trusted reviewer and guide across software and data engineering. As a small team, you'll also shape how we build our geospatial pipelines and internal analytics.
We're looking for someone who has designed and run data-intensive systems in production, makes sound architectural calls, and raises the bar for the engineers around them. You'll work closely with fellow software and data engineers, data scientists and solutions engineers, turning research code into robust, reproducible infrastructure. You will join a cross-functional, mission-driven team dedicated to bringing transparency and integrity to climate action.
Impact you’ll own:
* Shorten the path from experiment to production: own how models and estimation features move from research into reproducible, auditable client deliverables, with data, models and environments versioned end to end.
* Own our developer platform and engineering standards: environments, containers, project templates, CI/CD and pipeline orchestration across a multi-repo Python stack.
* Own our GCP infrastructure: architecture, infrastructure-as-code, monitoring, cost and access management, and its evolution as the company grows.
* Shape our geospatial workflows: how we store and process vector and high-resolution raster data at scale, and how the databases behind our models and deliverables evolve as we scale.
* Be the key reviewer for core and pipeline infra: write design docs for your own areas and review those of others, keeping our architecture coherent as the team grows.
* Raise the bar across engineering: mentor other engineers, and support our software & data engineering team with feedback and guidance on design and architecture.
* Over time, coordinate our infrastructure development goals: set priorities and align work across software and data engineering.
What you bring:
* 6+ years of experience in engineering roles, including significant time designing and running data-intensive backend systems and pipelines in production
* A track record of owning systems end to end: you've made architectural decisions and lived with their consequences, written and reviewed design docs, and mentored other engineers
* Expert Python and strong SQL, with solid experience designing schemas and data models for production systems
* Hands-on experience with workflow and pipeline tooling (e.g. Airflow, Dagster), experiment tracking and data versioning
* Hands-on experience running production cloud infrastructure, ideally GCP; infrastructure-as-code (e.g. Terraform/OpenTofu), IAM, as well as containers and reproducible environments (e.g. Docker, devcontainers)
* Deep experience across the software development lifecycle (Python packaging, containers, testing strategies, CI/CD, observability) and opinions on how to do it well
* Clear, direct communication with both technical and non-technical colleagues, and strong motivation to contribute to sustainable development through technology
* A degree in Software Engineering, Computer Science, or equivalent practical experience
### What makes you stand out:
* Production experience with raster data and geospatial pipelines
* Experience building model serving, model registries or other MLOps tooling (e.g. DVC, MLFlow)
* Experience building BI or dashboarding tooling (e.g. Streamlit) for non-technical users
* Experience with data warehouse design (e.g. BigQuery, PostgreSQL, dbt) and data engineering workflows
* Previous exposure to earth observation, environmental monitoring or soil science data
Benefits you can expect:
* Real ownership and influence over technical direction at an early-stage company
* Be part of a highly motivated, committed, and international team working on one of society’s biggest challenges: climate change
* Witness and shape the evolution of a new business being built
* An engineering culture built on designs docs, thoughtful code reviews and shared practices
* Remote-friendly: up to 4 days/week remote when based in Berlin, or fully remote from elsewhere in Germany, with flexible hours
* Drinks, snacks, team events, and your choice of hardware
Our growing team is looking for a senior software engineer to lead the evolution of the infrastructure that turns our science into trustworthy climate results. In this role, you'll own the platform that takes our data, models and estimation methods from R&D to auditable client deliverables, and you'll be a trusted reviewer and guide across software and data engineering. As a small team, you'll also shape how we build our geospatial pipelines and internal analytics.
We're looking for someone who has designed and run data-intensive systems in production, makes sound architectural calls, and raises the bar for the engineers around them. You'll work closely with fellow software and data engineers, data scientists and solutions engineers, turning research code into robust, reproducible infrastructure. You will join a cross-functional, mission-driven team dedicated to bringing transparency and integrity to climate action.
Impact you’ll own:
* Shorten the path from experiment to production: own how models and estimation features move from research into reproducible, auditable client deliverables, with data, models and environments versioned end to end.
* Own our developer platform and engineering standards: environments, containers, project templates, CI/CD and pipeline orchestration across a multi-repo Python stack.
* Own our GCP infrastructure: architecture, infrastructure-as-code, monitoring, cost and access management, and its evolution as the company grows.
* Shape our geospatial workflows: how we store and process vector and high-resolution raster data at scale, and how the databases behind our models and deliverables evolve as we scale.
* Be the key reviewer for core and pipeline infra: write design docs for your own areas and review those of others, keeping our architecture coherent as the team grows.
* Raise the bar across engineering: mentor other engineers, and support our software & data engineering team with feedback and guidance on design and architecture.
* Over time, coordinate our infrastructure development goals: set priorities and align work across software and data engineering.
What you bring:
* 6+ years of experience in engineering roles, including significant time designing and running data-intensive backend systems and pipelines in production
* A track record of owning systems end to end: you've made architectural decisions and lived with their consequences, written and reviewed design docs, and mentored other engineers
* Expert Python and strong SQL, with solid experience designing schemas and data models for production systems
* Hands-on experience with workflow and pipeline tooling (e.g. Airflow, Dagster), experiment tracking and data versioning
* Hands-on experience running production cloud infrastructure, ideally GCP; infrastructure-as-code (e.g. Terraform/OpenTofu), IAM, as well as containers and reproducible environments (e.g. Docker, devcontainers)
* Deep experience across the software development lifecycle (Python packaging, containers, testing strategies, CI/CD, observability) and opinions on how to do it well
* Clear, direct communication with both technical and non-technical colleagues, and strong motivation to contribute to sustainable development through technology
* A degree in Software Engineering, Computer Science, or equivalent practical experience
### What makes you stand out:
* Production experience with raster data and geospatial pipelines
* Experience building model serving, model registries or other MLOps tooling (e.g. DVC, MLFlow)
* Experience building BI or dashboarding tooling (e.g. Streamlit) for non-technical users
* Experience with data warehouse design (e.g. BigQuery, PostgreSQL, dbt) and data engineering workflows
* Previous exposure to earth observation, environmental monitoring or soil science data
Benefits you can expect:
* Real ownership and influence over technical direction at an early-stage company
* Be part of a highly motivated, committed, and international team working on one of society’s biggest challenges: climate change
* Witness and shape the evolution of a new business being built
* An engineering culture built on designs docs, thoughtful code reviews and shared practices
* Remote-friendly: up to 4 days/week remote when based in Berlin, or fully remote from elsewhere in Germany, with flexible hours
* Drinks, snacks, team events, and your choice of hardware
Skills Required
- 6+ years of experience in engineering roles, including substantial experience designing and operating data-intensive backend systems and production pipelines
- Experience owning systems end to end, making architectural decisions, writing and reviewing design documents, and mentoring engineers
- Expert Python and strong SQL skills, including production schema and data model design
- Hands-on experience with workflow and pipeline tools such as Airflow or Dagster, experiment tracking, and data versioning
- Hands-on experience operating production cloud infrastructure, ideally GCP, including infrastructure-as-code, IAM, containers, and reproducible environments
- Deep software development lifecycle experience, including Python packaging, containers, testing strategies, CI/CD, and observability
- Clear, direct communication with technical and non-technical colleagues
- Strong motivation to contribute to sustainable development through technology
- Degree in Software Engineering, Computer Science, or equivalent practical experience
- Production experience with raster data and geospatial pipelines
- Experience building model serving, model registries, or MLOps tooling such as DVC or MLflow
- Experience building BI or dashboarding tools such as Streamlit for non-technical users
- Experience with data warehouse design, including BigQuery, PostgreSQL, or dbt, and data engineering workflows
- Exposure to earth observation, environmental monitoring, or soil science data
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The Company
What We Do
Seqana is a Berlin-based startup that leverages remote sensing and machine learning to build data-driven Monitoring, Reporting, and Verification (MRV) solutions for soil-based carbon removal projects.
