Data Engineer, Analytics | Ingénieur de données, analytique

Role overview

Responsibilities

• Build scalable ETL/ELT pipelines and maintain logical and physical data models for multiple analytical use cases.
• Define data quality frameworks, validation, monitoring, and upstream logging improvements.
• Establish data access, privacy, and security models aligned with company requirements and governance standards.
• Develop reusable data staging and visualization solutions for self-service exploration.
• Contribute to semantic services and metadata frameworks that standardize definitions and reduce duplication.
• Write, debug, and optimize SQL and programmatic queries on large-scale distributed query engines.
• Translate business requirements into robust data infrastructure with cross-functional partners.
• Propose standards and processes that improve data governance and metadata management.
• Improve shared integration frameworks through peer guidance, enhancements, and documentation.

Minimum qualifications

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

Preferred qualifications

• Experience with responsible and ethical AI practices, including risk assessment, bias mitigation, and quality reviews.
• Experience improving upstream data quality through logging design or structured instrumentation.
• Experience building self-service analytics platforms or interconnected dashboards for non-technical stakeholders.
• Ongoing development of AI skills, such as prompt/context engineering or agent orchestration, and awareness of emerging AI technologies.
• Experience with shared data infrastructure, semantic layers, or metadata systems at a large organization.
• Familiarity with stream processing frameworks such as Apache Spark, Flink, or equivalent.
• Ability to use AI tools to improve workflows and demonstrate measurable impact.

About Meta

Compensation

• The posting lists a base salary range of CA$131,000–CA$181,000 per year, plus bonus, equity, and benefits.
• Compensation depends on skills, qualifications, experience, and location.