Senior Data Engineer

Role overview

Responsibilities

• Design, build, and optimize scalable enterprise data solutions.
• Deliver data ingestion, transformation, integration, and lakehouse pipelines.

Required qualifications

• 10 or more years in data engineering and enterprise data platforms, and 10 or more years working with high-volume enterprise datasets and performance optimization.
• 10 or more years with Git, Azure DevOps or GitHub, and CI/CD practices for data engineering.
• 8 or more years with Databricks, Apache Spark/PySpark, Python, and SQL.
• 8 or more years with Azure Data Lake Storage, Azure Data Factory, and related Azure data services.
• Bachelor's degree in Computer Science or equivalent real-world experience.

Preferred qualifications

• Knowledge of data security, governance, RBAC, encryption, and lineage; Delta Lake, Unity Catalog, and Databricks Workflows; and ETL/ELT, modeling, integration, and data quality.
• AWS data engineering experience with services such as S3, Glue, Lambda, or Redshift is a plus.
• Communication, problem-solving, and documentation skills, with ability to work independently with minimal guidance.

Compensation

• The posting gives a Canada-based target compensation range of $88,528 to $110,660 and notes possible incentive compensation based on individual or company performance.
• The posting does not state a salary cadence.

Benefits

• The posting describes Canadian health and dental coverage, telemedicine, wellness credits, income protection, retirement savings, and other benefits.
• A remote work allowance is available to eligible employees.

Workplace information

• The employer says it hires locally where possible and that remote or hybrid options may be available depending on client requirements.
• Office attendance near an office or client site may be required for meetings or events; no specific arrangement is stated for this role.