Senior Python Engineer

Duration: 12-Month Contract (with high potential for extension) Location & Work Arrangement: Toronto, ON (Hybrid: 4 days per week on-site at the corporate office, 1 day work from home) Advantages High-Impact Enterprise Engineering Scope: Direct the design and engineering of scalable microservices and data pipelines that power high-volume enterprise platforms. Modern Cloud & Data Tech Stack: Work extensively with FastAPI, Kubernetes, Kafka, Azure Databricks, PySpark, and Delta Lake in a cloud-native ecosystem. 12-Month Engagement Stability: Secure a full 1-year consulting engagement within a well-funded, stable enterprise technology group. Collaborative Environment: Partner closely with platform architects, security leads, and business stakeholders to establish reusable developer frameworks and automated delivery pipelines. Responsibilities Microservices & API Engineering Scalable Service Development: Design, build, and maintain secure, high-concurrency Python microservices and APIs using FastAPI, REST/gRPC, Docker, Kubernetes, Redis, and Kafka. Enterprise Integration: Deliver microservice APIs, internal platform APIs, data ingestion endpoints, event-driven streaming services, batch processing engines, and OAuth/security interfaces. Data Platform Modernization & Quality Data Pipeline Optimization: Build and optimize cloud data solutions using Python, PySpark, Azure Databricks, Delta Lake, ADLS, Azure Data Factory, Airflow, Azure SQL, and Unity Catalog. Reusable Frameworks & Automation: Develop shared frameworks, orchestration patterns, automated testing suites, and documentation to raise delivery quality across engineering teams. Operational Excellence: Perform root-cause troubleshooting, performance tuning, release support, and monitoring to maintain production platform resilience and compliance. Qualifications Professional Experience: 10+ years of software engineering experience, including strong, hands-on Python development within complex enterprise environments. Microservices & API Depth: Proven experience designing and delivering Python-based microservices and platform capabilities using FastAPI, REST/gRPC, Docker, Kubernetes, Redis, and Kafka. Data Engineering Expertise: Demonstrated experience building data solutions using Python, PySpark, Azure Databricks, Delta Lake, ADLS, Azure Data Factory, Airflow, Azure SQL, Unity Catalog, and SQL. Production Governance: Proven track record delivering secure, production-ready applications that adhere to enterprise standards for authentication, authorization, CI/CD testing, monitoring, and compliance. Education: University degree in Computer Science, Software Engineering, Mathematics, or a related technical discipline. Preferred Assets & Nice-to-Haves Experience designing scalable services or data pipelines that process high-volume enterprise workloads. Background building reusable internal developer platform capabilities or shared framework libraries. Exposure to AI-assisted engineering practices (e.g., GitHub Copilot) to accelerate coding, testing, and documentation. Strong communication skills with the ability to articulate technical design decisions to security, platform, and business partners.