Senior Data Engineer at Canadian Bank Note Company designing scalable cloud data platforms. Responsibilities include building data pipelines, ensuring data quality, and providing technical mentorship.
Responsibilities
Design, build, and maintain scalable cloud‑native data pipelines supporting batch and near‑real‑time use cases.
Engineer and optimize data ingestion, transformation, and orchestration pipelines using Azure Data Factory, Microsoft Fabric, Databricks, and related services.
Implement and maintain lakehouse and medallion architectures (bronze, silver, gold) to support analytics and AI workloads.
Develop robust transformation logic using SQL, PySpark, and Python with a focus on performance and maintainability.
Partner with Analytics/BI Engineers to ensure datasets are optimized for semantic layers and AI consumption.
Collaborate with data scientists to support feature engineering and model training workloads.
Implement data quality, validation, lineage, and observability solutions to ensure trust in data assets.
Design and enforce data security practices including access controls, encryption, and data classification.
Automate deployment and operations using DataOps and infrastructure‑as‑code practices.
Create and maintain technical documentation, runbooks, and architecture diagrams.
Provide technical leadership and mentorship to junior data engineers.
Requirements
Legally eligible to work in Canada.
Able to obtain Government of Canada Reliability or Secret security clearance.
Fluent in English (speak, read, write).
Bachelor's degree in Computer Science, Data Engineering, Software Engineering, or a related field.
Strong understanding of lakehouse, data warehouse, and medallion architecture patterns.
8+ years of relevant professional experience, including: 5+ years of professional experience in cloud data engineering or data platform roles.
5+ years of hands‑on experience with Microsoft Azure data services.
5+ years of experience building data pipelines using SQL and Python or PySpark. Working with structured and semi‑structured data.
Collaborating with analytics, BI, and AI teams.
Benefits
health, medical and life insurance benefits
defined contribution pension plan with company matching
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