Solutions Architect I, Professional Services
About this role
Professionals who thrive on solving complex spatial challenges and guiding customers through technical transformations will find a natural home in this role. Planet operates the largest constellation of imaging satellites in history, feeding empirical data into a cloud-based platform used globally across commercial, environmental, and humanitarian sectors. As a Solutions Architect, you will work within the Professional Services team to bridge the gap between technical capabilities and customer outcomes, leveraging your remote sensing and geospatial background to design robust architectures. You will collaborate closely with sales, engineering, and cross-functional stakeholders to pilot solutions, deliver workshops, and support pre-sales expansions, ensuring long-term value for clients.
What you will do
- Architect, design, pilot, and operationalize solutions that transform customer requirements into robust architectures aligned with business and technology strategies.
- Deliver workshops, tailored demo-apps, and workflows while designing user experiences for solution prototyping.
- Support pre-sales and customer expansions by leveraging remote sensing, geospatial, and AI knowledge.
- Act as the technical lead in solution development teams within Agile environments alongside project managers and software engineers.
- Liaise with cross-functional stakeholders, including product owners and image quality engineers, to architect optimal customer solutions.
- Collaborate with sales, marketing, and legal teams to support bidding and technical proposal writing for large projects.
- Champion company products through training, conference presentations, technical tutorials, and published articles.
What you need
- Bring 4 or more years of relevant work experience in a technical geospatial or remote sensing role.
- Hold a Bachelor's degree in GIS, Computer Science, Remote Sensing, Geography, or a related field.
- Demonstrate fluency in German and professional working proficiency in English.
- Possess extensive programming ability with Python for geospatial applications to process imagery and build data pipelines.
- Show experience with solution design, requirement gathering, and documentation.
- Display proficiency with common geospatial software such as QGIS, ArcGIS, GDAL, or ENVI.
Nice to have
- Advanced experience with machine learning algorithms applied to geospatial data, and the use of Claude and AI for geospatial application
- Working knowledge of modern cloud tools and pipelines, including Google Functions, CI/CD integrations, Vertex AI and Amazon Bedrock
- Knowledge of the Challenger methodology for liaising with clients
- Working knowledge of JavaScript and its mapping libraries such as OpenLayers, Leaflet, and ArcGIS API for JavaScript
- Familiarity with web development frameworks like React
Benefits
- Paid time off including vacation, holidays and company-wide days off
- Employee Wellness Program
- Home Office Reimbursement
- Monthly Phone and Internet Reimbursement
- Tuition Reimbursement and access to LinkedIn Learning
- Equity and Volunteering Paid Time Off
Skills and tech stack
Questions candidates ask
What is the remote work policy for this role?
This is a full-time, hybrid role which will require you to work from the Berlin office 3 days per week. Planet is a global company with employees working remotely worldwide and joining from various international offices.
What is the compensation and salary range?
The expected starting gross salary range for this role in Germany is €64.890 to €81.090 EUR. Individual placement is determined objectively based on skills, qualifications, and professional experience, and the role may also be eligible for discretionary bonuses, equity, and commission.
What domain knowledge and technical stack are expected?
You are expected to have a background in remote sensing, geoscience, or geoinformatics, along with extensive programming ability in Python for geospatial applications. Familiarity with cloud-computing environments like GCP, AWS, and Azure, as well as common geospatial software like QGIS and ArcGIS, is required.