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Python Developer (Singapore)

Summary

Build and scale containerized Python services on Kubernetes, setting up observability, CI/CD, and SRE practices for a 12-month deployment in Singapore.

Location: For deployment in Singapore; Visa Sponsorship is available

Our client is looking for a skilled Python Developer to join their team for a 12-month engagement. The successful candidate will play a pivotal role in the deployment and scaling of containerized workloads, utilizing Kubernetes and advanced observability tools. You will be responsible for managing the entire CI/CD lifecycle, ensuring high-performance, resilient systems through robust engineering practices.

Technical Requirements

  • Experience: 5+ years of Python development.

  • Core Competencies

    • Strong proficiency in Python programming language.

    • Hands-on experience with Kubernetes (deploying, managing, and scaling containerized workloads).

    • Strong background in observability, utilizing tools like Grafana, Prometheus, metrics, logs, traces, and alerting.

    • Experience with CI/CD tools (Git, Jenkins, GitHub Actions, TeamCity).

    • Expertise in scripting languages (Shell, Regular Expressions).

    • Working knowledge of Linux administration and troubleshooting.

    • Familiarity with open-source frameworks/libraries relevant to backend and platform development.

  • Methodology

    • Experience with Test-Driven Development (TDD).

    • Proficiency in Agile methodology (sprint planning, daily scrum, retrospectives, etc.).

  • Bonus/Exposure

    • Awareness of Docker, Ansible, Splunk/SIEM, and Public Cloud platforms.

    • Exposure to proxy, networking, or identity/authentication concepts (JWT, OAuth, SPIFFE) is a plus.

Project Milestones & Responsibilities. The role involves delivering critical outcomes across six key milestones:

  1. Observability & Initial Setup: Deploy solutions in Dev/QA/UAT, establish logging, monitoring, SIEM integration, and draft initial runbooks.

  2. Production Deployment: Deploy the Slipstream solution to Production, build/maintain automated CI/CD pipelines, and enable SRE monitoring dashboards.

  3. Scalability: Roll out Slipstream across multiple Kubernetes clusters, extend deployments to Windows/Linux, and standardize configuration patterns.

  4. Performance & Resiliency: Implement traffic-based autoscaling, enhance observability with alerts, and conduct stability/resiliency validation.

  5. Optimization: Continuous analysis of production telemetry, performance benchmarking, and fine-tuning resource utilization and latency.

  6. Documentation & Knowledge Transfer: Prepare technical/operational architecture documentation, create onboarding guides for consumer teams, and conduct training workshops.

See also

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