Lead Data Engineer at Toronto Hybrid

Elevate your career as a Lead Data Engineer with our team in Toronto, offering a hybrid work model. Drive innovative data solutions and architecture in an agile environment.

This Senior/Staff Data Engineer role entails developing robust data solutions while collaborating with business partners and stakeholders. You'll have a minimum of 8 years of experience in software and data engineering, complemented by expertise in Azure technologies including Data Factory, Databricks, and Azure DevOps. Your impact will facilitate fast, data-driven decision-making across the organization.

Key Responsibilities:

• • Design and implement scalable data solutions and analytics
• • Independently develop and ship complex features from start to finish
• • Build and maintain efficient data pipelines for various needs
• • Ensure data quality and integrity within data pipelines
• • Establish Azure infrastructure for self-service analytics

Requirements:

• • Minimum 8 years in software/data engineering
• • At least 2 years in a technical lead capacity
• • Strong understanding of data architecture patterns
• • Proficiency in Python and SQL, experience with PySpark
• • Knowledge of CI/CD practices using tools like Git
• Drive innovation and excellence in data engineering as part of our Toronto-based team.