Job Summary:
We are looking for a skilled 6+ years of experience Python Backend Developer with strong experience in API development and Google Cloud Platform (GCP). The role involves designing, developing, and deploying scalable, event-driven backend services using modern cloud-native architectures. The candidate will work in an Agile environment and collaborate with cross-functional teams to deliver high-quality solutions.
Key Roles & Responsibilities:
Design and develop RESTful APIs using Python frameworks such as Fast API or Flask
Build and deploy cloud-native applications on GCP (Cloud Run, GCS, Pub/Sub)
Implement event-driven architecture for scalable and decoupled services
Manage and secure cloud resources using IAM (GCP) best practices
Work with various data/file formats (JSON, CSV, XML, Parquet, Avro, PDF, Excel)
Containerize applications using Docker and manage artifacts via GCP Artifact Registry
Develop and maintain CI/CD pipelines using Git Hub Actions
Implement Infrastructure as Code (Ia C) using Terraform
Design, document, and maintain APIs using Open API/Swagger
Collaborate with QA and other teams for integration testing
Use AI-powered tools (Copilot, Claude, etc.) to improve development productivity
Participate actively in Agile ceremonies (scrum, sprint planning, reviews)
Ensure code quality using Git workflows, code reviews, and best practices
(Optional) Support/maintain services deployed on Kubernetes environments
Skills Required:
Primary Skills (Must Have):
Strong proficiency in Python
API development using Fast API / Flask
Hands-on experience with Google Cloud Platform (GCP)
Cloud Run
Cloud Storage (GCS)
Pub/Sub
IAM
Experience in REST API design & Open API/Swagger
Knowledge of event-driven architecture
Experience with Docker (containerization)
CI/CD experience using Git Hub Actions
Git version control & workflows
Understanding of Agile development methodologies
Terraform (Infrastructure as Code)
GCP Artifact Registry
Kubernetes
Experience handling multiple file formats (JSON, Parquet, Avro, etc.)
Exposure to AI-assisted development tools
or continue with email
We are looking for a skilled 6+ years of experience Python Backend Developer with strong experience in API development and Google Cloud Platform (GCP). The role involves designing, developing, and deploying scalable, event-driven backend services using modern cloud-native architectures. The candidate will work in an Agile environment and collaborate with cross-functional teams to deliver high-quality solutions.
Key Roles & Responsibilities:
Design and develop RESTful APIs using Python frameworks such as Fast API or Flask
Build and deploy cloud-native applications on GCP (Cloud Run, GCS, Pub/Sub)
Implement event-driven architecture for scalable and decoupled services
Manage and secure cloud resources using IAM (GCP) best practices
Work with various data/file formats (JSON, CSV, XML, Parquet, Avro, PDF, Excel)
Containerize applications using Docker and manage artifacts via GCP Artifact Registry
Develop and maintain CI/CD pipelines using Git Hub Actions
Implement Infrastructure as Code (Ia C) using Terraform
Design, document, and maintain APIs using Open API/Swagger
Collaborate with QA and other teams for integration testing
Use AI-powered tools (Copilot, Claude, etc.) to improve development productivity
Participate actively in Agile ceremonies (scrum, sprint planning, reviews)
Ensure code quality using Git workflows, code reviews, and best practices
(Optional) Support/maintain services deployed on Kubernetes environments
Skills Required:
Primary Skills (Must Have):
Strong proficiency in Python
API development using Fast API / Flask
Hands-on experience with Google Cloud Platform (GCP)
Cloud Run
Cloud Storage (GCS)
Pub/Sub
IAM
Experience in REST API design & Open API/Swagger
Knowledge of event-driven architecture
Experience with Docker (containerization)
CI/CD experience using Git Hub Actions
Git version control & workflows
Understanding of Agile development methodologies
Terraform (Infrastructure as Code)
GCP Artifact Registry
Kubernetes
Experience handling multiple file formats (JSON, Parquet, Avro, etc.)
Exposure to AI-assisted development tools
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