Lead Data Engineer at Manulife
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Summary
Lead Data Engineer at Manulife (insurance/financial services) in a hybrid role: design and maintain scalable data infrastructure, build orchestrated pipelines with quality controls, optimize platform performance, and support ML workflows. Core stack includes SQL, PySpark, Azure Data Factory, and Databricks, with close collaboration with business stakeholders and senior leadership.
Elevate your career as a Lead Data Engineer at Manulife in Montreal, Quebec. This hybrid role involves designing and optimizing data solutions while collaborating with business and technology teams to drive impactful analytics.
As a Senior Data Engineer, you will work closely with business stakeholders and fellow data professionals. Your responsibilities include creating scalable data pipelines, troubleshooting quality issues, and promoting data governance. The position offers significant exposure to senior leadership, allowing you to make meaningful contributions to the organization's data strategy.
Key Responsibilities: • Design and maintain scalable data infrastructure • Collaborate with teams to define data solutions • Implement data orchestration pipelines and quality control • Optimize data platform performance and reliability • Support machine learning workflows and analytics tools
Requirements: • Minimum 4 years as a data engineer or data scientist • Proficient in SQL and PySpark • Knowledge of NoSQL databases and data lakes • Experience with Azure Data Factory and Databricks • Familiarity with version control systems like Git
Make a difference with your data engineering expertise at Manulife.
As a Senior Data Engineer, you will work closely with business stakeholders and fellow data professionals. Your responsibilities include creating scalable data pipelines, troubleshooting quality issues, and promoting data governance. The position offers significant exposure to senior leadership, allowing you to make meaningful contributions to the organization's data strategy.
Key Responsibilities: • Design and maintain scalable data infrastructure • Collaborate with teams to define data solutions • Implement data orchestration pipelines and quality control • Optimize data platform performance and reliability • Support machine learning workflows and analytics tools
Requirements: • Minimum 4 years as a data engineer or data scientist • Proficient in SQL and PySpark • Knowledge of NoSQL databases and data lakes • Experience with Azure Data Factory and Databricks • Familiarity with version control systems like Git
Make a difference with your data engineering expertise at Manulife.