AZURE DATA ENGINEER

Job Description – Azure Databricks Data Engineer

Location: Toronto Downtown, Canada (Hybrid)

Experience: 6-10 Years

Job Summary

We are seeking an experienced Databricks Data Engineer to design, develop, and optimize enterprise-scale data platforms on Azure. The ideal candidate should have strong hands-on expertise in Azure Databricks, PySpark, Delta Lake, Azure Data Factory, and modern Lakehouse architectures. The role requires working closely with business stakeholders, data architects, and analytics teams to deliver scalable, high-performance data solutions.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using Azure Databricks and PySpark.
• Build and optimize ETL/ELT workflows for processing large volumes of structured and unstructured data.
• Develop and manage Delta Lake-based Lakehouse solutions following Medallion Architecture (Bronze, Silver, Gold).
• Integrate data from multiple sources including databases, APIs, cloud storage, and enterprise applications.
• Create and maintain data ingestion frameworks using Azure Data Factory (ADF).
• Optimize Spark jobs, cluster configurations, and storage structures to improve performance and reduce costs.
• Implement data quality, validation, monitoring, logging, and alerting mechanisms.
• Collaborate with Data Architects and Business Analysts to gather and translate business requirements into technical solutions.
• Implement security, governance, and access controls using Unity Catalog and Azure security services.
• Support CI/CD deployment processes using Azure DevOps, Git, and automated release pipelines.
• Participate in code reviews, design discussions, and knowledge-sharing initiatives.
• Troubleshoot production issues and provide operational support for critical data pipelines.

Mandatory Skills

Databricks & Big Data

• Azure Databricks
• Apache Spark
• PySpark
• Spark SQL
• Delta Lake
• Databricks Workflows
• Unity Catalog

Azure Data Services

• Azure Data Factory (ADF)
• Azure Data Lake Storage (ADLS Gen2)
• Azure Key Vault
• Azure Synapse Analytics

Programming & Database

• Python
• SQL / T-SQL
• Data Modeling
• Data Warehousing Concepts

DevOps & Version Control

• Azure DevOps
• Git/GitHub
• CI/CD Pipelines

Preferred Skills

• Snowflake
• Microsoft Fabric
• Kafka/Event Streaming
• Power BI
• Terraform/IaC
• Azure Functions
• REST API Integration
• Data Governance and Metadata Management

Desired Experience

• 6+ years of overall Data Engineering experience.
• Minimum 3+ years of hands-on experience with Azure Databricks and PySpark.
• Experience building enterprise-grade Lakehouse architectures.
• Strong understanding of performance tuning and optimization techniques for Spark workloads.