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Data Engineer Azure Databricks Jobs in Ontario (NOW HIRING)

Scotiabank

Data Engineer

Toronto, ON · On-site

You will work primarily on Spark based data processing running on Azure Databricks, developing ... This is an engineering heavy role for someone who enjoys writing clean, efficient code and ...

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All JobsData Engineer Azure Databricks JobsData Engineer Azure Databricks Jobs in Ontario

Data Engineer Azure Databricks information

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

AspectData Engineer Azure DatabricksData Analyst
Primary FocusBuilding data pipelines, data processing, and infrastructure using Azure DatabricksAnalyzing data to generate reports and insights
Skills & CertificationsAzure certifications, Spark, SQL, Python, ETL toolsSQL, Excel, BI tools, data visualization
Work EnvironmentCloud platforms, big data environments, collaborative teamsBusiness intelligence tools, data visualization platforms, reporting environments

While Data Engineer Azure Databricks focuses on developing scalable data pipelines and managing big data infrastructure on Azure, Data Analysts primarily interpret data to support business decisions. Both roles require strong analytical skills, but Data Engineers work more on data architecture and processing, whereas Data Analysts focus on data interpretation and reporting.

Infographic showing various Data Engineer Azure Databricks job openings in Ontario as of June 2026, with employment types broken down into 1% As Needed, 92% Full Time, 3% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Data Engineer - Spark, Databricks & Snowflake - DESDSAS

NavitasPartners

Hamilton, ON

$30/hr

Other

Posted 11 days ago

Job description

Job Title: Data Engineer - Spark, Databricks & Snowflake

Position Overview:
We are seeking a Data Engineer with strong expertise in modern data platforms to build scalable data pipelines and cloud-based data solutions for banking, financial services, and insurance clients.

Key Responsibilities:

  • Design and develop enterprise-grade data pipelines using Spark and Databricks.
  • Build and optimize Snowflake data warehouse solutions.
  • Develop ETL/ELT frameworks for structured and unstructured data.
  • Implement data quality, governance, and security controls.
  • Integrate data from core banking, payments, lending, risk, and regulatory systems.
  • Optimize data processing performance and cloud costs.

Required Skills:

  • Apache Spark (PySpark/Scala)
  • Databricks
  • Snowflake
  • SQL, Python
  • Azure/AWS/GCP Data Services
  • Data Modeling
  • ETL/ELT Development
  • CI/CD and DevOps Practices
  • Data Lake Architecture

Required Qualifications:

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • 5+ years of Data Engineering experience.
  • Experience implementing enterprise data platforms.

Mandatory Industry Experience:

  • Must have prior BFSI experience supporting banking, insurance, capital markets, lending, payments, wealth management, or risk management functions.


For more details reach at resumes@navitassols.com

Apply