| Lead Python Developer with GCP - 12 years Profile at Remote, Remote, USA |
| Email: [email protected] |
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From: Shivam Pachauri, Tek inspirations LLC [email protected] Reply to: [email protected] Job Description - Must have Expert Level GCP Cloud architecture Need LinkedIn profiles with submittal! Screener is Indian, we need only those consultants who can take technical screening by themselves. They caught proxy. PV will take Technical video Screening Lead Python Developer with Strong GCP C2H 100% Remote U.S. Citizen and GC Need 12 years or more experience. Must have Expert Level GCP Cloud architecture GCP, python, Flask, Dataflow, Fast API need 8 years of experience. Expert Lead Python developer Flask- Flask is called a "micro" framework because it provides the essentials for web development but leaves many other functionalities to be added through extensions and Fast- FastAPI is built on top of standard Python type hints and modern Python features, making it a powerful tool for developing APIs quickly and efficiently. Web APIs: Allow communication over HTTP, created with frameworks like Flask, Django, or FastAPI. Library APIs: Expose functions and classes within Python libraries. Operating System APIs: Provide access to OS features via modules like os and sys. Database APIs: Enable interaction with databases using libraries like SQLAlchemy. RESTful and GraphQL APIs: Two popular styles of APIs for web services. Skilled in system design- For a Python-based system, this could include scripts, libraries, APIs, and other software modules. Expert in GCP dataflow- Integrated with GCP Services: Dataflow integrates seamlessly with other GCP services, like BigQuery, Cloud Storage, and Pub/Sub, enabling a comprehensive data processing ecosystem. GCP cloud infrastructure- Google Compute Engine (virtual machines), Google Kubernetes Engine (container orchestration), and Google App Engine (platform-as-a-service) fall under this category. These provide the computational power needed to run applications and services. Jenkins- Automatically processing with Jenkins, CI/CD pipeline, Groovy, Kubernetes and other DevOps tools such as Docker container, Git/Github, and script in Unix/Linux environment. You can use Python to trigger Jenkins jobs using the Jenkins REST API. Trigger Jobs: Use Python to start Jenkins jobs through REST API calls or libraries like python-jenkins. Check Status: Query Jenkins for build status and job information. Python Libraries: Utilize libraries like python-jenkins for easier interaction with Jenkins. Pipelines: Integrate Python scripts into Jenkins pipelines for automated builds and tests. Logs and Notifications: Automate the retrieval of logs and manage notifications based on build outcomes. Groovy- Groovy Calling Python: Use Groovys execute() method to run Python scripts. Python in Jenkins Pipelines: Incorporate Python scripts into Jenkins pipelines using Groovy. Generating Groovy Code: Use Python to generate Groovy scripts dynamically. Data Exchange: Exchange data between Python and Groovy using files or other methods. Python Calling Groovy: Use Pythons subprocess to execute Groovy scripts. Integrating Python with Groovy allows you to leverage the strengths of both languages and build more flexible and powerful automation solutions. Keywords: continuous integration continuous deployment information technology green card Lead Python Developer with GCP - 12 years Profile [email protected] |
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| 11:50 PM 09-Dec-24 |