As of November 7, 2026, Jobsy lists 9 principal data engineer jobs in Canada. The most active employers are Altus Group Limited/Groupe Altus Limitée, Astra North Infoteck Inc. and Autodesk. Skills often requested: data engineering, ml, sql and aws.
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12+ YOECandidates need 12+ years in data engineering, including 8 years designing enterprise data platforms, plus experience as a technical leader on large programs. Cloud experience on Google Cloud Platform, AWS or Azure, and familiarity with DevOps and CI/CD are required.
Data engineering, ML, Sales, Regulatory compliance, Anti-money laundering, Data warehousing
10+ YOECandidates need a bachelor's degree in a technical field and at least 10 years of data engineering experience. They should have expert SQL and data-modelling skills, strong Python, and deep cloud expertise, preferably with Microsoft Azure.
Azure Data Factory, Databricks, Azure Synapse, Microsoft Fabric, Azure Data Lake, Azure DevOps
Candidates need advanced Python and SQL, plus Scala or Java, and hands-on Databricks, Apache Spark, and Delta Lake experience. They also need deep cloud platform expertise in AWS, Azure, or GCP, Terraform and CI/CD skills, and knowledge of IAM, encryption, and responsible AI.
Databricks, Apache Spark, Delta Lake, MLflow, PyTorch, TensorFlow
10+ YOEAutodesk needs candidates with 10+ years of data engineering or distributed systems experience, strong Python, Spark and advanced SQL skills, and hands-on AWS and streaming experience. Experience with LLM ecosystems, vector databases and RAG is also required.
Ledgebrook: Ledgebrook is a fully-remote US based company backed by top venture investors including Brand Foundry & American Family Ventures.
10+ YOECandidates need 10+ years in data or analytics engineering, expert Python and SQL, and production experience with Airflow, dbt, Terraform and Snowflake. They should own platform architecture end to end and build data quality and governance frameworks at scale.
12+ YOECandidates need 12–18 years of data engineering experience, including 5+ years with Databricks and Spark at scale and 8+ years with enterprise data warehouse and data lake platforms. Strong skills in PySpark, Spark SQL, Delta Lake, CI/CD and AWS or Azure are expected.
12+ YOECandidates need 12 to 18 years of data engineering experience, with deep Databricks, Spark, Delta Lake and PySpark skills. They also need legacy Cloudera migration experience, finance and risk data modelling, and cloud (AWS or Azure) and CI/CD experience.
Databricks, Apache Spark, PySpark, Delta Lake, Cloudera, Hive
10+ YOECandidates need 10+ years of data engineering experience, including 3 to 5 years at a principal or staff level in a start-up. They need production experience with Snowflake and dbt, expert Python and SQL, and strong AWS and data modeling skills.
Candidates need extensive experience running data engineering solutions in production, strong skills in Python, SQL and Spark, and practical Databricks experience. They should have created standards or platform capabilities adopted across teams, and ideally have worked with finance, credit or commercial real estate data.