Job Description

Python Software Developer (Data) 




 Data Pipeline Development
 



 Commodities Trading
 



 Toronto, Canada
 



  





 Our client, a prominent financial services firm, is looking for a
 Python Software Developer 
 to join their data focussed team. This role is focused on designing, developing, and maintaining
 ETL pipelines 
 to streamline the ingestion and processing of
 fundamental data 
 . This mid-level position offers the opportunity to work on impactful data infrastructure projects in a collaborative, front-office environment.
 



  





Responsibilities 



* Develop, implement, and optimize 
 robust data pipelines using Python to process and integrate large volumes of fundamental data.
* Build and maintain ETL pipelines 
 that support various analytical and operational applications by ingesting, cleaning, and transforming data.
* Collaborate with cross-functional teams 
 and key stakeholders, including data analysts, quantitative researchers, and other software developers, to ensure data pipelines align with business requirements and data quality standards.
* Ensure scalability and reliability 
 of the data infrastructure to meet the demands of high-quality, real-time data.
* Apply best practices 
 in software engineering, including code reviews, version control, automated testing, and continuous integration to deliver clean, maintainable, and efficient code.



  





  





Technical Skills & Qualifications 



* Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.
* Proficiency in Python 
 for data processing and pipeline development, with a strong understanding of libraries like Pandas and SQLAlchemy.
* Experience with
 SQL 
 and relational databases (e.g., PostgreSQL) for data storage, manipulation, and retrieval.
* Familiarity with
 ETL processes 
 and tools, and experience building ETL pipelines to handle high volumes of data.
* Knowledge of
 cloud development 
 environments, preferably AWS, for handling data ingestion and storage at scale.
* Familiarity with
 containerization technologies 
 (e.g., Docker, Kubernetes) to support scalable and flexible deployment.
* Experience with
 Apache Airflow 
 for orchestrating complex data workflows.
* Data transformation skills 
 , with a solid understanding of data quality, cleaning, and validation techniques.
* Strong problem-solving skills and the ability to communicate technical concepts effectively within a team.



  





  





Preferred Experience 



* Prior experience working with fundamental data in the financial sector, such as corporate earnings data, macroeconomic indicators, and other non-price-based financial data.
* Familiarity with front-office environments, ideally within finance, where high-quality data drives decision-making.
* Knowledge of data architecture best practices and experience in building scalable, maintainable data pipelines.