Sr Software Engineer-

Success in this role will be measured primarily by the delivery of high-quality, maintainable, well-tested, and production-ready Python software, along with improved software reuse, automation, platform reliability, and developer productivity., * Design, develop, test, deploy, and maintain production-quality Python applications, APIs, libraries, packages, and reusable components.

• Apply object-oriented programming, modular architecture, design patterns, and clean-code principles to create maintainable, extensible, and scalable software.
• Demonstrate advanced Python proficiency, including classes, modules, functions, data structures, type hints, packaging, dependency management, exception handling, and asynchronous or parallel-processing concepts.
• Implement standardized patterns for logging, configuration management, command-line interfaces, input validation, error handling, and failure recovery.
• Develop reusable frameworks, utilities, templates, and self-service capabilities that reduce duplication and improve developer productivity.
• Write comprehensive unit, integration, and regression tests using appropriate mocking, fixtures, automation, and code-coverage practices.
• Diagnose software defects, runtime failures, and performance bottlenecks; conduct root-cause analysis and implement sustainable remediation.
• Design, configure, deploy, and support containerized applications on Kubernetes in AWS, Azure, or comparable public-cloud environments.
• Use Infrastructure as Code tools such as Terraform, AWS CloudFormation, or Azure Resource Manager templates to automate cloud and platform infrastructure.
• Build and maintain CI/CD workflows using technologies such as GitHub, Jenkins, and Artifactory for source control, testing, packaging, artifact management, deployment, and release automation.
• Implement structured logging, metrics, dashboards, monitors, and alerts to support highly available and operationally reliable applications and platforms.
• Apply secure software-development practices, including peer reviews, dependency management, vulnerability remediation, secrets protection, and secure cloud configuration.
• Apply relational database concepts and SQL skills when designing application persistence, integrations, or data-processing solutions.
• Participate in technical design reviews, architecture discussions, code reviews, and the definition and adoption of engineering standards.
• Collaborate with software engineers, platform engineers, architects, support teams, and business stakeholders to translate evolving requirements into effective software solutions.
• Produce technical designs, application documentation, operational procedures, troubleshooting guides, and root-cause analysis records.
• Use AI-assisted development tools, including coding copilots and large language models, to improve development, testing, documentation, code review, and troubleshooting.

Experience with Kubernetes troubleshooting, cloud-platform engineering, high-availability design, application performance testing, and enterprise observability platforms is preferred., Demonstrate strong problem-solving, communication, collaboration, and influencing skills, with a consistent focus on automation, software quality, reliability, and operational perfection.

• Experience developing enterprise Python applications, backend services, API integrations, automation tools, internal frameworks, or platform-engineering software is preferred.

skills:

Apache Airflow,AWS,Apache Spark,API integrations,application performance,APIs,release automation,Artifactory,Azure Resource Manager,backend services,clean-code principles,cloud environments,AWS CloudFormation,software reuse,code reviews,code review,command-line,configuration management,CI/CD workflows,logging,ELT pipelines,data-processing,data structures,input validation,distributed data,ETL,Python applications,GitHub,Infrastructure as Code tools,Jenkins,Kubernetes,large language models,Azure,Azure cloud,object-oriented programming,advanced Python,Python software,regression tests,relational database concepts,design patterns,software quality,software solutions,technical design reviews,engineering software,source control,vulnerability remediation,SQL skills,platform reliability,integrations,Terraform,communication,influencing skills,troubleshooting,strong problem-solving,reliability,collaboration,AWS,architecture,AI-assisted development,automation,automate,automation tools,Azure cloud,dashboards,dependency management,Diagnose,infrastructure,troubleshooting guides,packaging,metrics,platform engineering,root-cause analysis,scalable software,exception handling,error handling,testing,documentation