Full Stack Python Engineer

PythonEnd-to-End Application LifecycleProduction EngineeringApplication IntegrationObservabilityGitHubDockerKubernetesAmazon Web Services (AWS)Microsoft AzureGoogle Cloud Platform (GCP)

Description

GSPANN is hiring a Full Stack Python Engineer to build, deploy, and run reliable business applications, focusing on smooth system integrations, stable production performance, and fast issue resolution.

Roles and Responsibilities

  • Design scalable Python-based applications and services, and write clean, maintainable, production-ready code.
  • Develop solutions, Application Programming Interfaces (APIs), integrations, and supporting utilities for Enterprise Resource Planning (ERP), infrastructure, and enterprise application environments.
  • Build and troubleshoot integrations between applications and enterprise systems using Representational State Transfer (REST) APIs, JavaScript Object Notation (JSON), and Extensible Markup Language (XML).
  • Support integration troubleshooting across application, API, and infrastructure layers, drawing on a clear view of end-to-end application flows, dependencies, and integration points.
  • Collaborate with application and platform teams to ensure reliable end-to-end system operation.
  • Drive applications independently from development through deployment and production, using GitHub and Git-based workflows for source code management and deployment.
  • Implement and operate workloads on Kubernetes and Docker container platforms, including pods, deployments, services, configurations, secrets, and basic troubleshooting.
  • Support reliable application releases through Continuous Integration / Continuous Delivery (CI/CD) pipelines and cloud and container platforms.
  • Ensure production stability by understanding how applications behave in production and troubleshooting application, integration, and deployment issues across the technology stack.
  • Drive technical Root Cause Analysis (RCA) during incident management, analyzing logs, metrics, and application behavior to identify production issues.
  • Optimize application reliability, performance, and maintainability by identifying recurring issues and reducing operational effort.
  • Implement application monitoring using Application Performance Monitoring (APM), logging, metrics, and observability tools, tracking health indicators such as availability, latency, error rates, throughput, and resource utilization.
  • Build logging, metrics, and telemetry into applications during development, configure dashboards and alerts for production visibility, and use observability data to troubleshoot issues and support RCA.
  • Support OpenSearch and Elasticsearch environments where applicable, including application-to-platform dependencies and basic operational considerations for search and logging platforms.

Skills and Experience

  • Bring 6+ years of software engineering experience with strong hands-on Python development.
  • Demonstrate a strong understanding of application development, production engineering, REST APIs, and application integrations.
  • Apply hands-on experience taking applications from development through deployment and production support.
  • Work with Git, GitHub, Kubernetes, and Docker in hands-on delivery.
  • Develop Python-based automation for operational activities.
  • Utilize application instrumentation, telemetry, and observability tools such as Dynatrace, AppDynamics, Datadog, New Relic, Grafana, Prometheus, Splunk, or similar APM, logging, and monitoring platforms.
  • Demonstrate strong production monitoring, troubleshooting, problem-solving, and RCA capabilities.
  • Apply Infrastructure as Code (IaC) to deploy Python applications to Kubernetes.
  • Work with CI/CD pipelines and cloud platforms such as AWS, Microsoft Azure, or GCP.
  • Bring hands-on experience with OpenSearch or Elasticsearch.
  • Utilize Helm, GitHub Actions, and Argo CD or other GitOps tools, which is an advantage.
  • Bring frontend experience with React, Angular, or similar frameworks, which is an advantage.
  • Manage Kubernetes troubleshooting and OpenSearch or Elasticsearch administration, which is an advantage.
  • Work with enterprise ERP and infrastructure integrations, which is an advantage.
  • Apply Site Reliability Engineering (SRE) practices, Service Level Indicators (SLIs), Service Level Objectives (SLOs), and reliability engineering, which is an advantage.

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