Azure Data Engineer

3 days ago

Toronto ON MJ E, Canada Apptad Inc Full time

Job Title: Azure Data EngineerLocation: Toronto, ONThis 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 Type: Full-time

Pay: $55.00-$56.00 per hour

Benefits:

  • Dental care
  • Paid time off

Experience:

  • Azure Data Factory: 5 years (required)
  • Databricks: 5 years (required)
  • CI/CD and IaC: 5 years (required)
  • PySpark and Python: 6 years (required)

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