Original job description
Our client, is seeking an experienced, high-performing Senior Python Engineer to join their core technology and platform engineering division.
In this senior engineering role, you will be responsible for designing, developing, and maintaining secure, cloud-native Python microservices, scalable APIs, and modern data engineering pipelines. You will bridge backend application development and big data infrastructure, utilizing tools such as FastAPI, Docker, Kubernetes, Redis, Kafka, Azure Databricks, PySpark, and Delta Lake. Operating within a collaborative engineering environment, you will build reusable frameworks, optimize event-driven architectures, enforce strict authentication/authorization security standards, and support operational excellence across mission-critical enterprise systems.
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.
Summary
If you are a tech-savvy Senior Python Engineer who pairs 10+ years of software development experience with expertise in FastAPI microservices, Kubernetes, Kafka, and Azure Databricks data engineering, this 12-month hybrid contract in Toronto is an outstanding opportunity. Bring your microservices precision, data pipeline architecture skills, and collaborative mindset to our client's technology team today!
Randstad Canada is committed to fostering a workforce reflective of all peoples of Canada. As a result, we are committed to developing and implementing strategies to increase the equity, diversity and inclusion within the workplace by examining our internal policies, practices, and systems throughout the entire lifecycle of our workforce, including its recruitment, retention and advancement for all employees. In addition to our deep commitment to respecting human rights, we are dedicated to positive actions to affect change to ensure everyone has full participation in the workforce free from any barriers, systemic or otherwise, especially equity-seeking groups who are usually underrepresented in Canada's workforce, including those who identify as women or non-binary/gender non-conforming; Indigenous or Aboriginal Peoples; persons with disabilities (visible or invisible) and; members of visible minorities, racialized groups and the LGBTQ2+ community.
Randstad Canada is committed to creating and maintaining an inclusive and accessible workplace for all its candidates and employees by supporting their accessibility and accommodation needs throughout the employment lifecycle. We ask that all job applications please identify any accommodation requirements by sending an email to accessibility@randstad.ca to ensure their ability to fully participate in the interview process.
This posting is for existing and upcoming vacancies.