Data Engineer, Analytics | Ingénieur de données, analytique

Role overview

Responsibilities

• Build scalable ETL and ELT pipelines, data models, data staging, and self-service visualization solutions.
• Establish data quality, monitoring, privacy, security, access, governance, semantic, and metadata frameworks.
• Optimize SQL and programmatic queries on distributed data engines and translate business needs into data infrastructure.
• Identify system gaps, improve shared integration frameworks and documentation, and guide peers on best practices.

Minimum qualifications

• 5+ years of data engineering experience designing and implementing production-grade ETL or ELT pipelines.
• 5+ years writing and optimizing SQL queries against large-scale distributed data systems.
• Experience designing logical and physical data models for multiple analytical use cases at scale.
• Experience implementing data quality processes, data access controls, and privacy-compliant data handling.
• Experience coding in Python, Scala, or a comparable language for maintainable, testable data pipelines.

Preferred qualifications

• Experience with responsible AI practices, upstream data quality, or structured application instrumentation.
• Experience building self-service analytics platforms or interconnected dashboards for nontechnical users.
• Ongoing AI skill development, including prompt or context engineering and agent orchestration.
• Experience with shared data infrastructure, semantic layers, or metadata systems at large organizations.
• Familiarity with Apache Spark, Flink, or equivalent stream processing; experience using AI tools to improve workflows.

Compensation

• Compensation is listed as CA$131,000–CA$181,000 per year, plus bonus, equity, and benefits.
• Individual compensation depends on skills, qualifications, experience, and location.

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