Data Integration Engineer

GFT TECHNOLOGIES SE; Montreal (administrative region); On-site; CAD 90,000 - 130,000; Full time

Job summary

GFT Technologies SE in Montreal, Canada is seeking a hands-on Data Integration Engineer to design, develop, and support enterprise data integration solutions within an Azure and Databricks ecosystem.

The role emphasizes delivery and operational support, building scalable pipelines, ensuring data quality, lineage, and governance, and collaborating with cross-functional teams across the data platform.

Qualifications

• 5-8 years of experience in Data Engineering, Data Integration, or Data Platform Development.
• Strong hands-on experience with Azure Databricks and Databricks notebooks.
• Proven experience building and supporting enterprise-scale data pipelines.
• Solid understanding of modern data lake and lakehouse architectures.

Responsibilities

• Design, develop, and maintain scalable data integration pipelines using Azure and Databricks.
• Build and support batch and near real-time data ingestion from multiple source systems.
• Develop data transformation logic to support analytics, reporting, and business needs.
• Implement data quality, validation, reconciliation, and monitoring processes.
• Collaborate with Data Engineers, Solution Architects, and stakeholders.

Skills

SQL

Python

Data Integration & ETL/ELT Development

Data Quality & Reconciliation

Tools

Azure Databricks

Databricks notebooks

Spark

Data lakehouse

Job description

Data Integration Engineer

Position Overview

We are seeking a hands-on Data Integration Engineer to join our growing data and analytics team. This role is focused on the design, development, enhancement, and support of enterprise data integration solutions within an Azure and Databricks ecosystem.

The ideal candidate is an execution-oriented professional who enjoys building and supporting data pipelines, integrating data from multiple source systems and implementing scalable modern data platform solutions. While the role requires participation in solution discussions, the primary focus is on delivery, implementation, and operational support, rather than enterprise architecture or strategic consulting.

Key Responsibilities

• Design, develop, and maintain scalable data integration pipelines using Azure and Databricks.
• Build and support batch and near real-time data ingestion processes from multiple internal and external source systems.
• Develop data transformation logic to support analytics, reporting, and business consumption requirements.
• Implement data quality, validation, reconciliation, and monitoring processes.
• Optimize pipeline performance and troubleshoot production issues.

Databricks Development

• Develop and maintain Databricks notebooks, workflows, and processing pipelines.
• Build transformation frameworks using Spark and Databricks best practices.
• Support data ingestion, cleansing, enrichment, and aggregation activities.
• Work with large and complex datasets across multiple domains.
• Support deployment, monitoring, and operational activities across the data platform.
• Implement and support Medallion Architecture (Bronze, Silver, Gold layers).
• Ensure data lineage, governance, and consistency across the platform.
• Contribute to data modeling and solution design discussions.
• Translate architectural direction into technical implementation and delivery.
• Collaborate closely with Data Engineers, Solution Architects, Product Owners, and Business Stakeholders.
• Support ongoing initiatives and enhancements within an established delivery team.
• Participate in Agile ceremonies, sprint planning, estimation, and backlog refinement.
• Assist in production support, troubleshooting, and continuous improvement initiatives.

Required Qualifications

• 5-8 years of experience in Data Engineering, Data Integration, or Data Platform Development.
• Strong hands-on experience with Azure Databricks.
• Proven experience building and supporting enterprise-scale data pipelines.
• Strong understanding of data ingestion, transformation, and integration patterns.
• Experience integrating data from multiple source systems and platforms.
• Solid understanding of modern data lake and lakehouse architectures.
• Experience implementing Medallion Architecture concepts.
• Strong SQL development and data analysis skills.
• Experience working within Agile delivery teams.

Technical Skills

Required

• SQL
• Python
• Data Integration & ETL/ELT Development
• Data Quality & Reconciliation

Preferred

• CI/CD for Data Pipelines
• Git
• Kafka or Event-Driven Architectures
• Power BI

Preferred Experience

• Experience supporting cloud-based analytics and reporting platforms.
• Experience working with complex enterprise data ecosystems.
• Exposure to financial services, insurance, banking, or regulated industries.
• Experience supporting production environments and ongoing operational initiatives.
• Familiarity with data governance and data management best practices.