Hybrid Data Engineer Role in Toronto
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Summary
Intermediate Data Engineer (4-6 years experience) in Toronto on a hybrid model, joining a Data & Analytics team serving a wealth-tech client in the financial sector. Day to day: building ETL/ELT pipelines, designing scalable AWS + Snowflake architectures, and supporting data quality, governance, and cloud migration using SQL, DBT, and Airflow.
Drive data solutions as an Intermediate Data Engineer in Toronto with a hybrid work model. Help shape advanced analytics and data governance within the Financial sector.
Our client seeks an Intermediate Data Engineer to join their Toronto-based Data & Analytics team. This role requires 4-6 years of hands-on experience in data engineering, specifically in designing and optimizing ETL/ELT pipelines. You'll work closely with analysts to ensure solutions meet the organization's technical needs for improved data visibility and governance.
Key Responsibilities:
• Build and maintain efficient ETL/ELT data pipelines
• Collaborate with teams to translate business requirements into data solutions
• Design scalable data architectures using AWS and Snowflake
• Ensure data quality and governance are maintained
• Assist in cloud migration initiatives
Requirements:
• 4-6 years of data engineering experience
• Strong SQL skills; experience with Snowflake or Databricks
• Knowledge of DBT and Airflow
• Familiar with CI/CD and data monitoring tools
• Experience in financial services is a plus
Contribute to data innovation within a leading organization in wealth tech.
Our client seeks an Intermediate Data Engineer to join their Toronto-based Data & Analytics team. This role requires 4-6 years of hands-on experience in data engineering, specifically in designing and optimizing ETL/ELT pipelines. You'll work closely with analysts to ensure solutions meet the organization's technical needs for improved data visibility and governance.
Key Responsibilities:
• Build and maintain efficient ETL/ELT data pipelines
• Collaborate with teams to translate business requirements into data solutions
• Design scalable data architectures using AWS and Snowflake
• Ensure data quality and governance are maintained
• Assist in cloud migration initiatives
Requirements:
• 4-6 years of data engineering experience
• Strong SQL skills; experience with Snowflake or Databricks
• Knowledge of DBT and Airflow
• Familiar with CI/CD and data monitoring tools
• Experience in financial services is a plus
Contribute to data innovation within a leading organization in wealth tech.