Senior Python Developer (Platform team)

About you

You are a proactive engineer who takes full ownership of your work and thrives in a fast-paced environment. You enjoy taking ambiguous problems, scoping them clearly, and proposing solid technical directions. You value clean architecture, type safety, and asynchronous collaboration. As a strong communicator, you act as an internal resource to help unblock other teams and provide direct, actionable, and kind feedback during code and design reviews.

About the project

We are looking for a Senior Python Developer to join the Platform Team working on a cloud-based SaaS product in the oil and energy domain. You will build reliable infrastructure solutions, work with heavy data processing toolchains, and contribute to internal core systems where structural scaling supports better technical decisions. 

Your area of responsibility

• Designing and implementing decoupled, maintainable services using SOLID principles and clean architecture in practice.
•  Building clean REST or gRPC services with OpenAPI contracts, while managing versioning to avoid breaking downstream consumers.
• Developing application logic capable of large-scale data manipulation and connecting Python services to data warehouses like Snowflake or Databricks for ingestion and retrieval.
• Deploying services on Google Cloud Platform (Cloud Run, Cloud Functions, GCS) and keeping GitHub Actions pipelines fast, reliable, and maintainable.
• Writing Architecture Decision Records (ADRs) and design diagrams, representing technical decisions to non-platform audiences, and preparing to coordinate delivery expectations across teams.

Skills and requirements

• 5+ years of experience in backend software development with a deep focus on core engineering and architecture.
• Production-grade Python 3.13+ experience, utilizing type annotations and async/await as the default with no shortcuts on type safety.
• Hands-on experience with Flask and/or FastAPI for building production services, a deep understanding of the tradeoffs between them, and comfort configuring Gunicorn for WSGI deployment.
• Hands-on experience with Polars, PyArrow, or Apache Iceberg for heavy data processing within applications.
• Proven experience deploying on GCP (Cloud Run, Cloud Functions, GCS) along with Docker and Docker Compose for local and lean production containerization.
• Strict enforcement of standards via ruff and pyright static analysis, alongside comprehensive pytest suites using fixtures, parameterization, and mocked external services.
• Experience with uv (or similar) for fast package resolution/virtual environments, and Bash scripting for build automation and local dev tooling.
• Ability to translate business constraints into engineering tradeoffs and explain technical decisions clearly to both platform and non-platform audiences.

Will be a plus

• Experience building or integrating with LLM orchestration tools and AI Agent Frameworks to enhance platform automation.