Lead design and delivery of enterprise-scale, cloud-native Azure data platforms. Architect and build Synapse/Databricks-based data lakes, warehouses, and ETL/ELT pipelines for batch and streaming. Drive data modernization, governance, performance optimization, and mentor data engineering teams while collaborating with cloud, DevOps, security, and analytics stakeholders.
Lead Data Engineer – Azure Data Platform
Location: Vaughan, ON (Hybrid)
Job Summary
We are seeking a highly experienced Lead Data Engineer to lead the design, development, and implementation of scalable, cloud-native data solutions on Microsoft Azure.
The ideal candidate will possess deep expertise in Azure Data Engineering services, modern data architecture, analytics platforms, and enterprise data warehousing solutions.
This role requires strong hands-on technical capabilities, leadership experience, and the ability to collaborate with business stakeholders, architects, and engineering teams to deliver high-quality data platforms supporting analytics, reporting, and operational workloads.
Key Responsibilities
Lead the design and implementation of enterprise-scale data platforms leveraging Microsoft Azure services.
Architect and develop scalable data solutions using Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage Gen2, Azure SQL Database, Azure Databricks, and related Azure services.
Design and develop robust ETL/ELT pipelines for batch and real-time data processing.
Build and maintain enterprise data warehouses, data lakes, and analytical data platforms.
Collaborate with business stakeholders to gather data, reporting, and integration requirements.
Define and implement data architecture standards, governance controls, security, and best practices.
Lead data modernization initiatives, including migration of legacy on-premises data platforms to Azure
Integrate data from ERP systems, operational applications, IoT platforms, APIs, and third-party data sources.
Optimize data pipelines, storage, and query performance to support large-scale analytics workloads.
Ensure platform reliability, scalability, security, and operational excellence.
Mentor and guide Data Engineers through architecture reviews, code reviews, and technical best practices.
Work closely with Cloud, DevOps, Infrastructure, Security, and Analytics teams to deliver end-to-end solutions.
Participate in solution architecture reviews, governance processes, and technical leadership forums.
Required Skills
10+ years of experience as a Data Engineer with strong expertise in Microsoft Azure Data Platform
Hands-on experience with Azure Synapse Analytics, Azure Data Factory, Azure Data Lake, Azure SQL, Databricks
Strong experience in Data Engineering, Data Warehousing, ETL / ELT development
Strong programming skills in SQL, Python, Spark, or PySpark
Experience with cloud architecture and distributed data processing pipelines
Experience leading or mentoring data engineering teams
Experience working with large-scale enterprise data platforms
Experience with Power BI, Fabric Analytics, or other data visualization tools
Experience with CI/CD, DevOps, Terraform, or Infrastructure as Code
Experience working with real-time / streaming / IoT data pipelines
Experience with Databricks, Spark, Delta Lake, or Lakehouse architecture
TechBlocks Vaughan, Ontario, CAN Office
Suite 4,, 399 Applewood Crescent, , , Vaughan, Ontario , Canada, L4K 4J3
Similar Jobs
Artificial Intelligence • Machine Learning • Retail • Social Impact • Software
Lead design and implementation of large-scale ETLs and data integrations for Distribution Center products using PySpark and DBT. Define DC data architecture, mentor engineers, manage contractors, and collaborate with product and applied science teams to improve onboarding, data quality, tooling, and scalability to power machine learning solutions.
Top Skills:
DatabricksDbtPysparkPythonSnowflakeSQL
Artificial Intelligence • Cloud • Hardware • Machine Learning • Quantum Computing
The Lead Data Engineer will design and enhance data pipelines and infrastructure for data-driven decisions, mentor engineers, and establish data governance.
Top Skills:
AirflowDagsterDatabricksDbtDelta LakeFivetranHudiIcebergPrefectPythonSnowflakeSQL
Fintech
Design and build reusable, metadata-driven data and AI engineering frameworks using Databricks and cloud-native services. Architect and deploy Delta Live Tables, Lakeflow, and orchestrated Databricks workflows for automated data processing and AI agent deployment. Implement RAG/Graph RAG solutions and agent orchestration (AgentOps, Agent-bricks, LangGraph), integrate real-time streams, manage AI agent lifecycles, and ensure governance via Unity Catalog or AWS Glue.
Top Skills:
Agent-BricksAgentic SystemsAgentopsAWSAws BedrockAws GlueAws SagemakerDatabricksDatabricks WorkflowsDelta Live TablesGraph RagLakeflowLakehouse ArchitectureLanggraphMcpMwaaRagStep FunctionsUnity Catalog
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.
