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Iris Software Inc.

senior Python Developer

  • Toronto, ON, Canada
  • Greater Toronto Area, Canada, Canada

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English
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Original job description

Senior Python Developer

Location: Toronto Ontario- hybrid 4 days

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Job Summary

Job 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, you'll 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 ClickHouse 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 ClickHouse 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: Strong 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 DevOps practices. Background in financial services or capital markets data systems.

Thanks & Regards,

Navin Singh

Recruiter – Talent Acquisition Group

Phone: 973-370-7023

Address: 200 Metroplex Drive, Suite 300, Edison, NJ 08817

Mail: Navin.singh@irissoftware.com

www.irissoftware.com

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More about this job

Responsibilities

Develop and optimize high-performance data processing workflows and pipelines using Python, pandas, polars, and ClickHouse. Build containerized and event-driven systems, implement distributed processing with Dask, and maintain code quality through testing and collaborative Git practices.

Requirements

Requires advanced Python proficiency, experience with pandas and polars, and hands-on knowledge of Docker, Kubernetes, ClickHouse or similar databases, NATS, pytest, Dask, and Git. Preferred qualifications include additional data science or machine learning libraries, CI/CD and DevOps experience, and a background in financial services or capital markets.

Skills

  • Python
  • Pandas
  • Polars
  • Docker
  • Kubernetes
  • ClickHouse
  • NATS
  • Pytest
  • Dask
  • Git
  • Data Pipeline Development
  • Distributed Computing
  • Data Processing
  • Unit Testing
  • Containerization
  • Event-Driven Architecture

Visa sponsorship

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Hiring contact

Navin Singh

Hiring contact email

Navin.singh@irissoftware.com

Categories

  • Software
  • Technology
  • Data & Analytics
  • Finance & Accounting

Keywords

  • Python
  • Pandas
  • Polars
  • Docker
  • Kubernetes
  • ClickHouse
  • NATS
  • Pytest
  • Dask
  • Git
  • Data Engineering
  • Data Processing Pipelines
  • Large-Scale Datasets
  • Distributed Computing
  • Containerization
  • Event-Driven Architecture
  • Asynchronous Processing
  • Columnar Databases
  • OLAP
  • Unit Testing
  • Integration Testing
  • Code Coverage
  • CI/CD
  • DevOps
  • Data Science
  • Machine Learning
  • Financial Services
  • Capital Markets

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