We're Hiring: Senior Python Specialist
Location: United Arab Emirates (Remote)
Employment Type: Full-Time
Experience Level: Senior
Work Arrangement: Fully Remote
About UsWe are a globally focused organization committed to building secure, scalable, reliable, and high-performance digital platforms, data solutions, automation capabilities, and enterprise applications across diverse markets.
Our technology teams collaborate across Software Engineering, Data, AI, Cloud, DevOps, Security, Product, Architecture, and Operations to develop robust Python-based solutions that support critical business processes, intelligent applications, automation, and evolving customer requirements.
The RoleWe are seeking an experienced Senior Python Specialist to lead the design, development, optimization, modernization, and support of Python-based applications, services, automation platforms, data solutions, and integration capabilities.
The ideal candidate will combine advanced Python expertise with strong software-engineering practices, API development, cloud technologies, automation, data processing, application performance, testing, security, and production reliability.
Key Responsibilities
- * Design, develop, maintain, and optimize enterprise Python applications and services.
- Lead the technical implementation of complex Python-based software solutions.
- Translate business and technical requirements into scalable, maintainable, and secure Python architectures.
- Develop clean, readable, reusable, testable, and production-ready Python code.
- Apply modern Python language features, libraries, frameworks, and development practices.
- Design modular application components using appropriate software-engineering principles.
- Develop backend services, APIs, microservices, automation tools, data-processing applications, and integration components.
- Design and implement RESTful APIs and other enterprise integration interfaces.
- Develop asynchronous and event-driven Python applications where appropriate.
- Work with frameworks such as FastAPI, Django, Flask, or other relevant Python technologies.
- Apply object-oriented, functional, and other appropriate programming paradigms.
- Establish reusable Python libraries, modules, utilities, and internal development frameworks.
- Develop scalable applications capable of supporting high transaction volumes and concurrent workloads.
- Optimize application performance, memory utilization, concurrency, and response times.
- Conduct profiling, benchmarking, load testing, and performance analysis.
- Identify and resolve memory issues, inefficient processing, concurrency problems, and resource bottlenecks.
- Troubleshoot complex Python application failures, production incidents, and runtime issues.
- Analyze logs, stack traces, metrics, traces, diagnostic data, and application behavior.
- Conduct root-cause analysis and implement permanent corrective actions.
- Develop comprehensive unit, integration, functional, performance, and regression tests.
- Establish appropriate test automation practices for Python applications and services.
- Maintain high standards for code quality, readability, maintainability, and testability.
- Conduct detailed peer code reviews and provide constructive technical feedback.
- Establish Python coding standards, development guidelines, reusable patterns, and engineering best practices.
- Support architecture reviews and provide recommendations on Python technology choices.
- Evaluate Python versions, frameworks, libraries, packages, development tools, and technical approaches.
- Manage Python dependencies and ensure appropriate package versioning and compatibility.
- Monitor and address outdated, unsupported, or vulnerable Python dependencies.
- Support modernization of legacy Python applications and migration toward modern architectures.
- Refactor legacy code to improve maintainability, performance, scalability, reliability, and security.
- Integrate Python applications with relational and NoSQL databases.
- Optimize database access, queries, transactions, connection management, and data-processing workflows.
- Develop data pipelines, transformation processes, ingestion services, and automation workflows where required.
- Work with messaging systems, queues, event streams, caching platforms, and distributed services.
- Integrate Python applications with cloud platforms, external APIs, enterprise systems, and third-party services.
- Develop automation solutions for infrastructure, operations, testing, deployment, monitoring, and business processes.
- Support containerized Python applications using Docker, Kubernetes, or comparable platforms.
- Collaborate with DevOps teams to improve build, deployment, release, and operational processes.
- Contribute to CI/CD pipelines for automated Python application build, testing, security scanning, and deployment.
- Support infrastructure and environment automation using appropriate scripting and configuration tools.
- Implement application logging, monitoring, metrics, tracing, health checks, and observability capabilities.
- Establish appropriate alerts, diagnostics, dashboards, and operational monitoring for Python services.
- Apply secure coding practices and address application vulnerabilities and security findings.
- Collaborate with Security teams on authentication, authorization, encryption, secrets management, dependency security, and application hardening.
- Ensure Python applications comply with organizational security, architecture, development, and operational standards.
- Support production releases, deployments, upgrades, and emergency fixes.
- Participate in incident-management and production-support activities where required.
- Develop technical documentation covering architecture, APIs, configuration, deployment, troubleshooting, and operational procedures.
- Mentor Python developers and provide guidance on programming, architecture, debugging, performance, testing, and engineering practices.
- Conduct technical workshops and knowledge-sharing sessions for engineering teams.
- Collaborate with Product, Architecture, Infrastructure, Security, Data, AI, DevOps, and Operations teams.
- Provide technical estimates, implementation plans, risk assessments, and delivery updates.
- Identify opportunities to improve engineering productivity through automation, reusable components, tooling, and developer platforms.
- Evaluate emerging Python technologies and assess their applicability to business and technical requirements.
- Support Python-based data science, machine learning, AI, analytics, and scientific-computing initiatives where applicable.
- Establish appropriate development practices for Python projects involving data processing and computational workloads.
- Contribute to technology roadmaps and long-term Python platform modernization strategies.
- Provide technical leadership for complex Python initiatives and high-impact engineering projects.
Key Performance Indicators
- * Python application availability
- Application reliability
- API availability
- Application response time
- Transaction throughput
- Processing throughput
- Error rate
- Production incident frequency
- Mean time to detect incidents
- Mean time to resolve incidents
- Critical defect resolution time
- Application performance
- CPU utilization efficiency
- Memory utilization efficiency
- Processing resource efficiency
- Performance regression rate
- Automated test coverage
- Unit-test success rate
- Integration-test success rate
- Regression-test success rate
- Code-review completion
- Code-quality performance
- Static-analysis compliance
- Security vulnerability remediation time
- Dependency vulnerability rate
- Dependency currency
- Build success rate
- Deployment success rate
- Release stability
- CI/CD automation coverage
- Deployment frequency
- Change failure rate
- API defect rate
- Integration reliability
- Database performance
- Data-processing accuracy
- Data-pipeline reliability
- Automation success rate
- Observability coverage
- Monitoring and alert effectiveness
- Technical-debt reduction
- Legacy modernization progress
- Reusable component adoption
- Documentation completeness
- Engineering standards compliance
- Production support effectiveness
- Developer productivity improvements
- Automation savings
- Stakeholder satisfaction
- Knowledge-sharing and mentoring effectiveness
Ideal CandidateThe successful candidate should have strong experience in Python software development, backend engineering, automation, data engineering, application development, platform engineering, or Python-based enterprise solutions, preferably within technology, financial services, telecommunications, e-commerce, data-intensive, or other complex digital environments.
The candidate should demonstrate:
- Advanced proficiency in Python and modern Python development practices.
- Strong understanding of software-engineering principles and application architecture.
- Extensive experience with frameworks such as FastAPI, Django, Flask, or comparable technologies.
- Strong experience developing enterprise applications, backend services, APIs, microservices, and automation solutions.
- Deep understanding of Python data structures, functions, decorators, generators, exceptions, modules, packages, and object-oriented programming.
- Strong understanding of asynchronous programming, concurrency, multiprocessing, and performance optimization.
- Experience profiling and diagnosing Python application performance issues.
- Strong knowledge of REST APIs, HTTP, JSON, authentication, authorization, and enterprise integration patterns.
- Experience with relational databases, SQL, transactions, ORM technologies, and database optimization.
- Familiarity with NoSQL databases, caching technologies, messaging platforms, and event-driven architectures.
- Experience with Kafka, RabbitMQ, Redis, or comparable technologies is desirable.
- Strong understanding of distributed systems and scalable application architectures.
- Experience with Docker, Kubernetes, cloud platforms, and containerized Python applications.
- Strong understanding of CI/CD and modern software-delivery practices.
- Experience with Git and contemporary source-control workflows.
- Strong knowledge of automated testing, mocking, integration testing, and performance testing.
