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.