Senior Python Developer

Python Developer Location: Toronto, ON Work Arrangement: Hybrid – 4 Days Onsite Experience: 8+ Years Position Overview We are seeking an experienced Python Developer to design, develop, and optimize scalable data services that support enterprise AI/ML applications. The ideal candidate will have strong software engineering fundamentals, distributed systems experience, and hands-on expertise with Python, SQL, Apache Spark, Docker, Kubernetes/OpenShift, and hybrid cloud environments. You will collaborate closely with infrastructure engineers, data engineers, and machine learning researchers to build reliable, high-performance data applications across cloud and on-premises environments. Key Responsibilities • Design, develop, and optimize scalable data services and applications supporting AI/ML workloads. • Architect and implement distributed systems and software services with a focus on scalability, reliability, performance, and maintainability. • Establish and follow software engineering best practices, including code reviews, unit/integration testing, design patterns, coding standards, and documentation. • Develop and deploy highly scalable applications using Python and modern software frameworks. • Build resilient data automation solutions across hybrid cloud and on-premises environments. • Collaborate with infrastructure teams and ML researchers to ensure seamless integration and reliable operation of data services. • Develop and optimize data access layers for SQL and NoSQL databases. • Work with databases such as MongoDB and relational database platforms in development and non-production environments. • Develop and optimize data processing solutions using Apache Spark and SQL. • Containerize and deploy applications using Docker and Kubernetes/OpenShift (OCP4). • Support application deployments across major cloud platforms, including AWS and Azure, as well as on-premises infrastructure. • Implement observability, monitoring, logging, and performance-management practices to improve system visibility and reliability. • Troubleshoot complex application, data, infrastructure, and performance issues across distributed environments. Must-Have Skills & Experience • Strong professional experience in Python development and software engineering. • Hands-on experience designing and implementing distributed systems, scalable architectures, and data services. • Strong understanding of software architecture, design patterns, code quality, testing, and code review practices. • Experience building and deploying scalable, production-grade applications and services. • Strong hands-on experience with Python, SQL, and Apache Spark. • Practical experience with Docker and Kubernetes or OpenShift Container Platform (OCP4). • Experience deploying applications across hybrid environments, including on-premises infrastructure and AWS/Azure. • Experience designing data access layers and integrating with relational and NoSQL databases. • Hands-on experience with MongoDB or comparable NoSQL databases. • Knowledge of observability, monitoring, logging, troubleshooting, and application performance practices. • Strong understanding of REST APIs, microservices, distributed applications, and cloud-native development. Preferred Qualifications • Experience supporting AI/ML platforms, data-intensive applications, or machine learning workloads. • Experience with CI/CD pipelines, Git, DevOps, and automated deployment practices. • Familiarity with cloud-native architecture and 12-factor application principles. • Experience working in large-scale enterprise environments with cross-functional engineering teams. • Strong problem-solving, communication, and collaboration skills. Key Technology Stack Python | SQL | Apache Spark | Docker | Kubernetes | OpenShift/OCP4 | AWS | Azure | MongoDB | SQL/NoSQL | REST APIs | Distributed Systems | Microservices | Observability | Monitoring | Logging | CI/CD | AI/ML