- Architect and build effective ETL pipelines in Python to process diverse data sources
- Implement data transformation logic using pandas for complex manipulations and aggregations
- Document pipeline architecture, data flows, and transformation processes
- Collaborate with data scientists and business stakeholders to understand data requirements
- Optimize existing pipelines for performance and maintainability
- Implement data quality checks and monitoring solutions
Required Skills
- Strong Python programming experience (3+ years)
- Advanced proficiency with pandas for data manipulation and analysis
- Experience designing and maintaining production ETL workflows
- Solid understanding of data modeling concepts and techniques
- Familiarity with SQL and relational database concepts
- Version control systems (Git) and collaborative development practices
Preferred Qualifications
- Experience with Polars for high-performance data processing
- Familiarity with DuckDB for analytical query processing
- Knowledge of cloud-based data platforms (AWS, GCP, or Azure)
- Experience with orchestration tools like Airflow, Luigi, or Dagster
- Understanding of data governance and compliance requirements
- Contributions to open-source data projects
What Makes You Successful
- Problem-solving mindset with attention to detail
- Strong communication skills to explain technical concepts clearly
- Commitment to code quality and testing practices
Ability to balance competing priorities in a fast-paced environment
📌 Data Scientist (Toronto)
🏢 LanceSoft
📍 Toronto
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