Azure Data Engineer

Job Title: Azure Data Engineer

Location: Toronto, ON (Hybrid)This role requires deep technical expertise in Azure data services, modern data architecture, and best practices in data engineering, security, and automation.Key Responsibilities:Architecture & Solution Design:

• Architect cloud-native data solutions using Azure Data Lake, Synapse, Databricks, and Data Factory.
• Define the end-to-end data architecture including ingestion, transformation, modeling, storage, and consumption layers.
• Lead the adoption of Delta Lake, lakehouse patterns, streaming architectures, and medallion models.
• Evaluate new Azure capabilities and make recommendations to improve data strategy and platform maturity.

Data Pipeline & Platform Development:

• Build highly scalable, fault-tolerant ETL/ELT pipelines using ADF, Databricks, Synapse pipelines, and Azure Functions.
• Write complex transformations using PySpark, SQL, Python, and Spark best practices.
• Optimize pipeline performance, cost efficiency, and reliability through tuning and automation.

Data Governance, Quality & Security:

• Establish data quality frameworks, validation rules, observability, and automated testing.
• Implement enterprise-grade security including RBAC, Key Vault integration, encryption, and audit controls.
• Work with governance teams to enable lineage, metadata management, and cataloging with Azure Purview.

Leadership & Collaboration:

• Mentor and guide junior/intermediate data engineers on Azure best practices.
• Partner with architects, data scientists, BI developers, and business teams to deliver high-impact data solutions.
• Lead technical design reviews, code reviews, and cloud architecture discussions.

DevOps & Automation:

• Develop CI/CD pipelines using Azure DevOps or GitHub Actions for automated deployment of data workloads.
• Create and maintain Infrastructure as Code (IaC) using ARM/Bicep or Terraform.
• Implement monitoring and logging using Azure Monitor, Log Analytics, and Databricks monitoring tools.

Required Qualifications:

• 7–12+ years of experience in data engineering or software engineering.
• Advanced experience with Azure Data Factory, Azure Databricks, Azure Synapse Analytics, ADLS Gen2.
• Expert proficiency in SQL, PySpark, and Python.
• Strong experience designing large-scale data architectures (lakehouse, data warehouse, streaming).
• Solid understanding of advanced ETL/ELT patterns, orchestration, and distributed computing.
• Proven experience optimizing Spark clusters, query performance, and cloud spend.
• Hands-on experience implementing CI/CD and IaC in Azure environments.
• Strong knowledge of Azure security best practices (managed identities, RBAC, networking, encryption).

Preferred Qualifications:

• Experience building streaming pipelines using Event Hub / Kafka / Spark Structured Streaming.
• Background enabling ML/AI data pipelines or feature stores.
• Familiarity with Power BI, semantic models, and analytics ecosystems.
• Azure certifications: DP-203, DP-500, AZ-305, or similar.
• Experience in regulated industries (finance, insurance, public sector).

Job Types: Full-time, Permanent

Pay: $55.00-$60.00 per hour

Benefits:

• Dental care
• Life insurance
• Paid time off

Experience:

• Azure: 5 years (required)
• Databricks: 5 years (required)
• Azure Synapse Analytics: 5 years (required)
• CI/CD : 3 years (required)