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
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Design, develop, and optimize scalable data services and applications supporting AI/ML workloads.
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Architect and implement distributed systems and software services with a focus on scalability, reliability, performance, and maintainability.
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Establish and follow software engineering best practices, including code reviews, unit/integration testing, design patterns, coding standards, and documentation.
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Develop and deploy highly scalable applications using Python and modern software frameworks.
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Build resilient data automation solutions across hybrid cloud and on-premises environments.
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Collaborate with infrastructure teams and ML researchers to ensure seamless integration and reliable operation of data services.
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Develop and optimize data access layers for SQL and NoSQL databases.
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Work with databases such as MongoDB and relational database platforms in development and non-production environments.
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Develop and optimize data processing solutions using Apache Spark and SQL.
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Containerize and deploy applications using Docker and Kubernetes/OpenShift (OCP4).
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Support application deployments across major cloud platforms, including AWS and Azure, as well as on-premises infrastructure.
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Implement observability, monitoring, logging, and performance-management practices to improve system visibility and reliability.
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Troubleshoot complex application, data, infrastructure, and performance issues across distributed environments.
Must-Have Skills & Experience
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Strong professional experience in Python development and software engineering.
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Hands-on experience designing and implementing distributed systems, scalable architectures, and data services.
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Strong understanding of software architecture, design patterns, code quality, testing, and code review practices.
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Experience building and deploying scalable, production-grade applications and services.
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Strong hands-on experience with Python, SQL, and Apache Spark.
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Practical experience with Docker and Kubernetes or OpenShift Container Platform (OCP4).
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Experience deploying applications across hybrid environments, including on-premises infrastructure and AWS/Azure.
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Experience designing data access layers and integrating with relational and NoSQL databases.
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Hands-on experience with MongoDB or comparable NoSQL databases.
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Knowledge of observability, monitoring, logging, troubleshooting, and application performance practices.
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Strong understanding of REST APIs, microservices, distributed applications, and cloud-native development.
Preferred Qualifications
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Experience supporting AI/ML platforms, data-intensive applications, or machine learning workloads.
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Experience with CI/CD pipelines, Git, DevOps, and automated deployment practices.
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Familiarity with cloud-native architecture and 12-factor application principles.
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Experience working in large-scale enterprise environments with cross-functional engineering teams.
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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
