Middle to Senior Python Engineer

In this role, you will contribute to the development of cloud-native applications and data engineering solutions while working with cutting-edge technologies in Google Cloud Platform and Kubernetes-based environments. You will collaborate with cross-functional teams to deliver scalable, secure, and high-quality solutions supporting critical business processes.

• Hands-on experience with Python development in production environments
• Knowledge of Python libraries and frameworks such as Pandas, Requests, FastAPI, and SQLAlchemy
• Proficiency with Google Cloud Platform and cloud-native solutions
• Expertise in Kubernetes, including kubectl, Helm, Google Kubernetes Engine, and containerized application deployment
• Experience with CI/CD tools and processes, including Terraform, Git/GitHub, GitHub Actions, Docker, and code review workflows
• Knowledge of SQL and experience working with relational and NoSQL databases such as PostgreSQL and MongoDB
• Understanding of cloud-based data warehousing solutions, including Google Storage and Google BigQuery
• Openness for working in Agile environments, including sprints, pull requests, and peer reviews

Nice to have:

• Experience with data engineering and pipeline solutions using Apache Airflow, Apache Beam, GCP Dataflow, and XML/JSON data ingestion

• Design, develop, and maintain Python-based applications and services to support cloud-native and data-driven solutions
• Build and optimize scalable data engineering pipelines using modern cloud and orchestration technologies to improve platform reliability and performance
• Collaborate closely with engineers, DevOps specialists, and stakeholders to deliver secure, maintainable, and high-quality software solutions
• Deploy, configure, and manage applications in Kubernetes environments using Helm and Google Kubernetes Engine
• Develop and maintain CI/CD pipelines using GitHub Actions, Terraform, Docker, and Git-based workflows
• Monitor and troubleshoot applications and infrastructure using ArgoCD, Prometheus, and Grafana
• Write clean, testable, and maintainable code following test-driven development practices with Pytest
• Analyze, enhance, and support existing complex codebases, including debugging and reverse-engineering components when needed