Job Description Python Developer – Data Engineering | Pandas, Polars, Docker, Kubernetes, Dask Toronto, ON - Hybrid (4 Days WFO) Role Description We are seeking a skilled Python Developer to join our data engineering team.

You will design, develop, and maintain high-performance data processing pipelines using modern Python frameworks and tools.

In this role, youll work with large-scale datasets, containerized systems, and distributed computing platforms to deliver robust data solutions.

Key Responsibilities • Develop and optimize data manipulation workflows using pandas and polars to handle large datasets efficiently. • Design and implement containerized applications using Docker and Kubernetes to ensure scalable, reliable deployments. • Build and maintain data pipelines integrating with Click

House columnar databases for analytical workloads. • Develop event-driven architectures using NATS messaging systems for asynchronous data processing. • Write comprehensive unit tests using pytest to ensure code quality and reliability. • Implement distributed computing solutions with Dask for processing data beyond single-machine memory constraints. • Manage version control using Git and collaborate on code repositories following best practices.

Required Skills and Experience Python & Data Processing:



Advanced proficiency in pandas and polars for data manipulation, transformation, and analysis.

Experience optimizing code performance for large datasets.

Containerization & Orchestration: Hands-on experience with Docker for building container images and composing multi-container applications.

Knowledge of Kubernetes for container orchestration and deployment management.

Data Infrastructure: Working knowledge of Click

House or similar columnar databases for OLAP workloads and analytical queries.

Messaging & Streaming: Familiarity with NATS.io for building message-driven systems and asynchronous workflows.

Testing & Quality Assurance: Proficiency with pytest for writing unit tests, integration tests, and maintaining code coverage standards.

Distributed Computing: Experience with Dask for parallel processing and handling out-of-core computations.

Version Control: Robust command of Git workflows, branching strategies, and collaborative development practices.

Preferred Qualifications • Experience with additional Python libraries for data science and machine learning. • Familiarity with CI/CD pipelines and Dev

Ops practices. • Background in financial services or capital markets data systems.

Requirements Java

📌 Python Developer – Data Engineering (Toronto)
🏢 Astra North Infoteck
📍 Toronto