Senior Data Engineer - Montreal

Job Description

Industrious is seeking a Senior Data Engineer to join their data team in Montreal. The Senior Data Engineer will be responsible for designing, building, and maintaining robust data pipelines and infrastructure. The ideal candidate will have deep expertise in modern data integration and transformation tools, including Snowflake, Stitch, and DBT. They will collaborate with cross-functional teams to ensure data availability, reliability, and scalability while optimizing data workflows.Role involves:

• Designing, developing, and maintaining scalable data pipelines using Stitch and FiveTran.
• Implementing and managing data transformation workflows using DBT.
• Optimizing and tuning Snowflake data warehouse performance.
• Implementing, maintaining and optimizing LookML data models.
• Collaborating with data analysts, data scientists, and business stakeholders.
• Ensuring data integrity, security, and compliance.
• Monitoring and troubleshooting data pipeline issues.
• Contributing to the continuous improvement of data engineering processes.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field (or equivalent experience).
• 5+ years of experience in data engineering or a related role.
• Proven expertise with Stitch and FiveTran for data integration and ETL processes.
• Strong proficiency in DBT for data modeling, transformation, and testing.
• Extensive hands-on experience with Snowflake.
• Strong knowledge and experience in event driven architecture using standard message queues.
• Familiarity with programming languages such as Python or Scala for data processing.
• Solid understanding of data pipeline architecture, cloud infrastructure, and best practices in data engineering.
• Excellent problem-solving skills and attention to detail.
• Ability to work independently and collaborate effectively in a team environment.

Role offers:

• Opportunity to work with modern data integration and transformation tools.
• Collaboration with cross-functional teams.
• Contribution to data-driven decision-making processes.
• Continuous improvement of data engineering processes, tools, and standards.