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Azure Data Engineer Jobs in Ontario (NOW HIRING)

MUST HAVES Must Haves: * 5+ years experience Azure environment * 5+ years experience Data engineering with ADF and Databricks * 5+ years experience Programming experience with Python, SQL Location: 3 ...

Data Engineer

Toronto, ON · Hybrid

CA$90K - CA$125K/yr

Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure ...

Senior Data Engineer

Toronto, ON · Hybrid

CA$120K - CA$145K/yr

Your deep knowledge of data platforms such as Azure Fabric, Databricks, and Snowflake will be essential as you collaborate closely with data analysts, scientists, and other engineers to ensure ...

Data Engineer I

Toronto, ON · On-site

CA$69K - CA$98K/yr

PySpark on Azure Data Factory, Azure Databricks, ADLS, and Delta Lake. * Own the reliability of ... Strong programming skills in Python, plus practical experience with Spark and * PySpark for large ...

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

Data Developer II

Windsor, ON · On-site

CA$35.06 - CA$46/hr

As a Data Developer II, you will be responsible for designing, implementing, and maintaining GEM ... Utilize cloud-native data services, including Azure Storage, to optimize data management and ...

The Data Engineer plays a critical role within the Enterprise Data & AI Technology organization-one ... Experience building data pipelines, and composable cloud-based data platforms (Azure), using Azure ...

The Data Engineer plays a critical role within the Enterprise Data & AI Technology organization-one ... Experience building data pipelines, and composable cloud-based data platforms (Azure), using Azure ...

Data Engineer I

Toronto, ON

CA$69K - CA$98K/yr

Azure Data Factory, ADLS, and Delta Lake. * Strong programming skills in Python, plus practical experience with Spark and * PySpark for large-scale data processing. * Solid grounding in relational ...

Showing results 21-40

Azure Data Engineer information

What is the difference between Azure Data Engineer vs Data Analyst?

AspectAzure Data EngineerData Analyst
Required CredentialsAzure certifications, SQL, Python, cloud skillsData analysis certifications, SQL, Excel, BI tools
Work EnvironmentCloud platforms, data pipelines, big data toolsData visualization, reporting, business insights
Industry UsageTech, finance, healthcare, retailMarketing, finance, healthcare, retail

Azure Data Engineers focus on building and maintaining data pipelines in cloud environments, utilizing tools like Azure Data Factory and SQL. Data Analysts interpret data to generate reports and insights, often using Excel and BI tools. While both roles work with data, Azure Data Engineers handle data infrastructure, whereas Data Analysts focus on data interpretation and visualization.

What are the key skills and qualifications needed to thrive as an Azure Data Engineer?

To thrive as an Azure Data Engineer, you need proficiency in data modeling, SQL, ETL processes, and a solid understanding of cloud computing concepts, typically supported by a degree in computer science or a related field. Familiarity with Microsoft Azure services (such as Azure Data Factory, Azure Synapse Analytics, and Azure Databricks), and relevant certifications like Microsoft Certified: Azure Data Engineer Associate, are highly valuable. Strong problem-solving skills, effective communication, and adaptability help you collaborate across teams and respond to evolving project needs. These skills are crucial for designing robust data solutions that support business intelligence and decision-making in cloud environments.

What are some common challenges Azure Data Engineers face when integrating data from multiple sources?

Azure Data Engineers often encounter challenges when consolidating data from diverse sources such as on-premises databases, cloud storage, and third-party applications. Issues like data format inconsistencies, varying data quality, and synchronization timing can complicate the integration process. Leveraging Azure services like Data Factory and Synapse Analytics helps automate and streamline these tasks, but careful planning and robust data validation are essential. Collaboration with business analysts and data architects is also crucial to ensure the integrated data meets organizational requirements.

What is an Azure Data Engineer?

Azure Data Engineers are IT professionals who design, implement, and manage data solutions using Microsoft Azure cloud services. They are responsible for building data pipelines, integrating diverse data sources, and ensuring data is stored securely and efficiently. These engineers work with tools like Azure Data Factory, Azure Databricks, and Azure Synapse Analytics to process, transform, and analyze large volumes of data. Their main goal is to provide reliable data infrastructure to support business intelligence and analytics needs.

Is an Azure Data Engineer a good career?

An Azure Data Engineer is a valuable role focused on designing and implementing data solutions using Microsoft Azure cloud services. It typically requires skills in data modeling, SQL, and tools like Azure Data Factory and Databricks, with certifications such as Microsoft Certified: Azure Data Engineer Associate enhancing job prospects. The role offers strong demand due to the increasing reliance on cloud-based data management and analytics.
What are the most commonly searched types of Azure Data Engineer jobs in Ontario? The most popular types of Azure Data Engineer jobs in Ontario are:
What are popular job titles related to Azure Data Engineer jobs in Ontario? For Azure Data Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Azure Data Engineer jobs in Ontario look for? The top searched job categories for Azure Data Engineer jobs in Ontario are:
Infographic showing various Azure Data Engineer job openings in Ontario as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, and 20% Remote job distribution.

Senior Data Engineer - Corporate Data Analytics Group

Canadian Bank Note Company

Nepean, ON • On-site, Remote

Full-time

Medical, Life, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

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 recruitment@cbnco.com 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 recruitment@cbnco.com .