Data Engineer building data integration pipelines for data lakes and warehouses. Collaborating with stakeholders to meet business requirements in a leading publishing company.
About the role
- Data Engineer role in Toronto requiring 2+ years experience with large datasets, Python optimization, and data integration. Hybrid work with 3 days on-site.
Responsibilities
- Exciting Opportunity: Data Engineer Location: Toronto – Hybrid (3 days on site) Candidate Requirements/Must Have Skills: 1. 2+ years of Solid experience working with large datasets and complex data transformations 2. 2+ years of experience with Python, with hands-on experience optimizing data-heavy workloads (Demonstrated ability to improve performance of existing code {e.g., pandas optimization, algorithmic improvements}) 3. 1+ years of Experience sourcing and integrating data from multiple systems or formats (e.g., files, databases, APIs) 4. Familiarity with best practices for writing clean, maintainable, and testable code Nice-To-Have Skills: 1. Experience with data engineering frameworks or tools (e.g., PySpark, Dask, Airflow)
Requirements
- Candidate Requirements/Must Have Skills: 1. 2+ years of Solid experience working with large datasets and complex data transformations 2. 2+ years of experience with Python, with hands-on experience optimizing data-heavy workloads (Demonstrated ability to improve performance of existing code {e.g., pandas optimization, algorithmic improvements}) 3. 1+ years of Experience sourcing and integrating data from multiple systems or formats (e.g., files, databases, APIs) 4. Familiarity with best practices for writing clean, maintainable, and testable code Nice-To-Have Skills: 1. Experience with data engineering frameworks or tools (e.g., PySpark, Dask, Airflow)
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