Remote Senior Data Engineer - Corporate Data Analytics Group

Company Description

Canadian Bank Note Company (CBN) is a leader and trusted provider of secure document and adjacent enterprise-level system solutions across the following domains: border security, civil identity, driver licence/identification and vehicle information, excise control, currency, lotteries and charitable gaming.

Our Corporate Philosophy and 7 Core Principles shape and guide our corporate behaviours and underpin the sense of community you will experience at CBN. We seek long-term relationships with our employees and offer a competitive compensation package that includes health, medical and life insurance benefits and a defined contribution pension plan with company matching.

Job Description

Job Title: Senior Data Engineer

Job Type: Permanent, Full-time

Location: Ottawa, Ontario

Work Model: Remote

Job Status: Existing Vacancy

Position Summary

The Senior Cloud Data Engineer is responsible for designing, building, and operating scalable, secure, and reliable cloud data platforms that power analytics, AI, and decision‑making across the organization. This role focuses on engineering high‑quality, production‑grade data pipelines and data products using Microsoft Azure, Microsoft Fabric, and Databricks, enabling downstream BI, Copilot, and AI/ML workloads.

Key Responsibilities

Data Pipeline & Platform Engineering

• 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.

Data Integration & Analytics Enablement

• 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.

Data Quality, Governance & Security

• 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.

DataOps, Automation & Cost Optimization

• Automate deployment and operations using DataOps and infrastructure‑as‑code practices.
• Optimize cloud performance and costs across the data platform.

Documentation & Operational Support

• Create and maintain technical documentation, runbooks, and architecture diagrams.

Leadership & Mentorship

• Provide technical leadership and mentorship to junior data engineers.

Qualifications

Mandatory Requirements

• Legally eligible to work in Canada.
• Able to obtain Government of Canada Reliability or Secret security clearance.
• Fluent in English (speak, read, write).

Minimum Qualifications

• 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.

Preferred Qualifications

• 10+ years of relevant professional experience
• Microsoft Certifications:
  • Fabric Analytics Engineer Associate (DP‑700) or Databricks Certified Data Engineer Associate or equivalent
• Knowledge of AI/ML data requirements and feature engineering.

• Experience with the following:
• Microsoft Fabric (OneLake, lakehouses, pipelines, notebooks).
• Azure Databricks for large‑scale data processing.
• DataOps and CI/CD for data platforms.
• Experience in manufacturing, software, or regulated environments.

Additional Information

Equal Opportunity Statement

Our organization is committed to employment equity and diversity in the workplace. We actively encourage applications from women, Indigenous Peoples, persons with disabilities, members of visible minorities, and LGBTQ2+ individuals.

We are dedicated to removing barriers and fostering an inclusive workplace that reflects society and we are committed to providing an accessible and inclusive recruitment process in accordance with the Accessibility for Ontarians with Disabilities Act (AODA).

If you require accommodation at any stage of the hiring process, please contact us at [email protected] so that appropriate arrangements can be made.

AI Use in Recruitment Statement

As part of our commitment to transparency and fairness in hiring, we disclose that artificial intelligence (AI) tools may be used at certain stages of our recruitment process. These tools assist in tasks such as resume screening, candidate matching, and interview scheduling. All AI-assisted decisions are subject to human oversight to ensure fairness, accuracy, and compliance with applicable laws.

We are committed to the responsible, transparent, and accountable use of AI, in alignment with Ontario’s Responsible Use of Artificial Intelligence Directive and the requirements under the Working for Workers Four Act. This includes taking steps to mitigate bias, protect candidate privacy, and ensure that AI does not unfairly influence hiring outcomes.

If you have questions or concerns about how AI is used in our hiring process, please contact us at [email protected] .