Role Overview:

Reporting to the Manager, Data Engineering, the Senior Data Engineer is responsible for designing, maintaining, and delivering scalable, high-performance data solutions that empower better, faster, and simpler decision-making across the organization. This role ensures data is reliable, accessible, and optimized for advanced analytics while driving innovation in data infrastructure. As a technical leader, the Senior Data Engineer will mentor team members, lead complex deployments, and collaborate with cross-functional partners to deliver impactful results aligned with our strategic goals.

Duties & Responsibilities:

Data Solutions & Pipelines:

• • Lead the development, optimization, and maintenance of data pipelines from multiple sources while building and enhancing database business logic, including stored procedures, triggers, and functions, to support efficient ETL/ELT processes for analytics and operations

Infrastructure & Cloud:

• • Manage modern data warehouses across AWS, Azure, and Snowflake while maintaining and enhancing AWS serverless pipelines—leveraging tools like Step Functions, Fargate, Lambda, SAM, and API integrations—with strong troubleshooting and debugging expertise.

DevOps & Automation:

• • You own the CI/CD deployment processes for Databricks jobs, serverless pipelines, and database scripts, while driving automation through tools such as Docker and Jenkins.

Advanced Analytics Enablement:

• • Develop and optimize pipelines to support ML models, simulations, and predictive analytics.

Governance & Documentation:

• • Ensure data governance best practices are applied to maintain quality, security, and compliance, while also producing comprehensive documentation that supports both developers and business users.

Leadership & Collaboration:

• • Mentor data engineers to strengthen their skills and foster collaboration, while partnering with analytics, IT, and business teams to ensure solutions align with strategic objectives.

Experience & Qualifications:

Education & Experience

• • Bachelor’s in Computer Science, Software Engineering, Data Science, or related field.
  • 6–8 years of data engineering experience with leadership in scalable solution delivery.

Technical Skills (Must-Have)

• • SQL Expertise — advanced stored procedures, triggers, functions, business logic in Snowflake, AWS RDS, or Azure SQL.
  • ETL Tools — Alteryx, Databricks, or equivalent.
  • Programming — Python or MySQL.
  • Cloud & Serverless — AWS, Azure, Snowflake, Step Functions, Fargate, Lambda, SAM, API integration.
  • DevOps — Own CI/CD for data workloads; experience with Docker/Jenkins.
  • Visualization — Tableau or Power BI.

Additional Skills

• • Experience supporting ML and predictive analytics pipelines.
  • Strong communication and problem-solving skills.
  • Proactive learner, adaptable to emerging technologies.
  • Bilingual
  • Proficiency in both written and verbal English communication is essential for effective correspondence with clients, suppliers, business partners, and colleagues beyond the province of Quebec.