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Added 8 mins ago
AWS Architect/ Tech Lead
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Toronto, ON
Full-time
…throughout the transformation lifecycle. You will work closely with senior business and technology stakeholders, architecture governance forums, and delivery teams to translate business…
Added 8 mins ago
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Full-time
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Direct mentorship from senior directors managing flagship green initiatives.
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Director of Communications
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Full-time
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Full-time
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Added 11 mins ago
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Added 41 mins ago
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$95,000 to $135,000 CAD / year
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Senior Manager, Supply Chain Management
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Propel

Data Engineer - Databricks - Full Time

Canada

Pay: CAD $115,000 to $150,000 Depending on Experience
Job type: Full-time
Experience: 5 to 7 years of experience in data engineering, including at least 2 to 4 years working directly with Databricks
Posting language: English
Posted: Sep 25, 2026

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Original job description

We are looking for experience Data Engineers to join a fast growing company within the Financial Sector.

If you have strong experience with Databricks please take a look!!

About the Role

We are looking for a Databricks Data Engineer on a Full Time basis to help build and maintain their data pipelines and lakehouse infrastructure. This is a hands on role that involves taking ownership of moderately complex data engineering tasks, working closely with senior engineers on architecture decisions and partnering with analysts and data scientists to deliver reliable, well modelled data.

Key Responsibilities

Build and maintain ETL/ELT pipelines using Databricks, Apache Spark and Delta Lake
Develop and support bronze, silver and gold layer data models within a Lakehouse architecture
Create and manage jobs and workflows using Lakeflow Jobs and Spark Declarative Pipelines (formerly Delta Live Tables)
Write clean, efficient PySpark and SQL code for data transformation and processing
Optimise Spark job performance through partitioning, caching and cluster configuration
Implement data quality checks and basic monitoring/alerting for pipeline health
Support data governance and access management using Unity Catalog, including permissions, lineage and catalog/schema structure
Participate in code reviews, follow CI/CD practices and manage deployments using Declarative Automation Bundles (formerly Databricks Asset Bundles)
Troubleshoot pipeline failures and data quality issues, escalating complex problems as needed
Document pipelines, data models and processes for team and stakeholder reference
Collaborate with analysts and data scientists to understand data requirements and deliver fit for purpose datasets

Technical Skills Required

5 to 7 years of experience in data engineering, including at least 2 to 4 years working directly with Databricks
Strong practical PySpark and SQL skills for data transformation
Understanding of Delta Lake and medallion (bronze/silver/gold) architecture
Familiarity with the Databricks platform, including Lakeflow, declarative pipeline based ETL tooling, job orchestration and Unity Catalog
Experience with at least one cloud platform (AWS, Azure or GCP)
Experience with Git based version control and CI/CD workflows using Databricks Asset Bundles
Understanding of data modelling and ETL/ELT design principles
Exposure to or interest in AI assisted workflows on the platform, such as setting up Genie spaces or building simple agents with Agent Bricks

Desirable Skills

Databricks Certified Data Engineer Associate or Professional
Experience with Spark Declarative Pipelines (or DLT) and Unity Catalog
Familiarity with orchestration tools such as Lakeflow Jobs, Airflow or Autosys
Basic understanding of streaming data concepts, including Structured Streaming
Experience with infrastructure as code (Terraform)
Degree or diploma in Computer Science, Engineering or a related field, or equivalent practical experience

Salary

CAD $115,000 to $150,000 Depending on Experience

Next Steps

If this sounds like a good match for you please submit your CV by clicking apply. If you have any questions please reach out directly.

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More about this job

Responsibilities

Build and maintain Databricks-based data pipelines, lakehouse models, and workflows, while optimizing Spark performance and implementing data quality checks, monitoring, and governance. Collaborate with senior engineers, analysts, and data scientists to deliver reliable datasets, support deployments and troubleshooting, and document data processes.

Requirements

Requires 5–7 years of data engineering experience, including 2–4 years working directly with Databricks, along with strong PySpark and SQL skills and knowledge of Delta Lake, medallion architecture, data modeling, and ETL/ELT principles. Candidates should have experience with at least one cloud platform, Git-based version control, and CI/CD; a relevant degree or diploma or equivalent practical experience is also noted.

Skills

Databricks
PySpark
SQL
Apache Spark
Delta Lake
Lakehouse Architecture
ETL/ELT Pipelines
Data Modeling
Lakeflow Jobs
Spark Declarative Pipelines
Unity Catalog
CI/CD
Cloud Platforms
Data Quality
Spark Performance Optimization
Git

Visa sponsorship

Not detected in the job text

Keywords

Databricks
Apache Spark
PySpark
SQL
Delta Lake
Lakehouse Architecture
Medallion Architecture
ETL/ELT
Data Pipelines
Data Modeling
Lakeflow Jobs
Spark Declarative Pipelines
Delta Live Tables
Unity Catalog
Databricks Asset Bundles
CI/CD
Git
AWS
Azure
GCP
Data Governance
Data Quality
Structured Streaming
Airflow
Autosys
Terraform
Genie
Agent Bricks
Financial Sector
Databricks Certified Data Engineer

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