💡 The Project

As a Senior Backend Python Engineer, you will join immediately to architect and scale their core energy data processing pipeline and real-time API orchestration layer.

This is a heavy systems-design role where you will not only write performant, asynchronous Python code but also shape the microservices architecture that handles millions of IoT data points daily.

You will collaborate closely with Data Scientists, DevOps, and Product teams to build highly scalable backend systems using Python (FastAPI), Kafka, and PostgreSQL, ensuring machine learning models are successfully integrated into production.

If you are a builder who values scalable architecture and wants to use your technical skills to fight climate change, then this is the role for you!

🎯 Responsibilities

• Architect & Scale: Design and implement high-performance, distributed backend services that process massive volumes of real-time sensor and grid data.
• Build & Ship: Write clean, reliable, and asynchronous code in Python using modern frameworks like FastAPI.
• Collaboration: Work closely with the Data Science team to productionize machine learning models and integrate them into the core product API.
• Data Pipelines: Optimize and manage data streaming architectures and relational databases to ensure low latency and high availability.
• Quality Assurance: Champion best practices in code reviews, automated testing, and CI/CD workflows to maintain a highly robust production environment.

💻 Tech Stack

• Backend: Python (FastAPI).
• Data & Messaging: PostgreSQL, Apache Kafka, Redis.
• Cloud & DevOps: AWS, Docker, Kubernetes, GitHub Actions.
• Testing: Pytest, mock frameworks.

🛠️ Your Experience

• 5+ years of professional software engineering experience.
• Deep Python Expertise: Extensive production experience building complex backend systems and RESTful/GraphQL APIs using modern Python.
• Distributed Systems: Hands-on experience with microservices architecture, asynchronous programming, and event-driven systems (Kafka, RabbitMQ, or similar).
• Database Mastery: Strong background in relational databases (PostgreSQL), complex query optimization, and schema design for time-series or heavy data loads.
• Cloud Native: Experience deploying and managing applications in containerized environments (Docker, Kubernetes) on AWS or GCP.
• Testing: Proven track record of ensuring high software quality through rigorous automated testing (Pytest) and clean architecture principles.

🧬 You will be a cultural fit if...

• You have a High-Ownership Mindset: Autonomous, proactive, and taking full responsibility for the systems you build from local development to production.
• You are a Critical Thinker: Someone who is not afraid to speak up, constructively challenge architectural decisions, and provide scalable solutions.
• You are Collaborative: Structured, goal-oriented, and enjoy mentoring junior engineers while working cross-functionally.
• You bring Enthusiasm: A strong passion for sustainability and a positive attitude toward solving hard technical problems.
• 
  

💡 The Project

As a Senior Backend Python Engineer, you will join immediately to architect and scale their core energy data processing pipeline and real-time API orchestration layer.

This is a heavy systems-design role where you will not only write performant, asynchronous Python code but also shape the microservices architecture that handles millions of IoT data points daily.

You will collaborate closely with Data Scientists, DevOps, and Product teams to build highly scalable backend systems using Python (FastAPI), Kafka, and PostgreSQL, ensuring machine learning models are successfully integrated into production.

If you are a builder who values scalable architecture and wants to use your technical skills to fight climate change, then this is the role for you!

🎯 Responsibilities

• Architect & Scale: Design and implement high-performance, distributed backend services that process massive volumes of real-time sensor and grid data.
• Build & Ship: Write clean, reliable, and asynchronous code in Python using modern frameworks like FastAPI.
• Collaboration: Work closely with the Data Science team to productionize machine learning models and integrate them into the core product API.
• Data Pipelines: Optimize and manage data streaming architectures and relational databases to ensure low latency and high availability.
• Quality Assurance: Champion best practices in code reviews, automated testing, and CI/CD workflows to maintain a highly robust production environment.

💻 Tech Stack

• Backend: Python (FastAPI).
• Data & Messaging: PostgreSQL, Apache Kafka, Redis.
• Cloud & DevOps: AWS, Docker, Kubernetes, GitHub Actions.
• Testing: Pytest, mock frameworks.

🛠️ Your Experience

• 5+ years of professional software engineering experience.
• Deep Python Expertise: Extensive production experience building complex backend systems and RESTful/GraphQL APIs using modern Python.
• Distributed Systems: Hands-on experience with microservices architecture, asynchronous programming, and event-driven systems (Kafka, RabbitMQ, or similar).
• Database Mastery: Strong background in relational databases (PostgreSQL), complex query optimization, and schema design for time-series or heavy data loads.
• Cloud Native: Experience deploying and managing applications in containerized environments (Docker, Kubernetes) on AWS or GCP.
• Testing: Proven track record of ensuring high software quality through rigorous automated testing (Pytest) and clean architecture principles.

🧬 You will be a cultural fit if...

• You have a High-Ownership Mindset: Autonomous, proactive, and taking full responsibility for the systems you build from local development to production.
• You are a Critical Thinker: Someone who is not afraid to speak up, constructively challenge architectural decisions, and provide scalable solutions.
• You are Collaborative: Structured, goal-oriented, and enjoy mentoring junior engineers while working cross-functionally.
• You bring Enthusiasm: A strong passion for sustainability and a positive attitude toward solving hard technical problems.