Senior Data Engineer

Toronto, ON
Hybrid
Posted Oct 7, 2026
1 position

$75–$80 / hour

Opens LinkedIn

Employment type: Contract
Experience level: Mid-level · 2+ years
Posting language: English
Working hours: 40 hours per week
Office presence: 3 days per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design, build, and maintain scalable Azure data pipelines, ETL/ELT processes, enterprise data warehouses, and integrations across multiple platforms. Collaborate with stakeholders, document technical standards, troubleshoot data issues, and contribute to cloud modernization and continuous improvement.

Job details

Data Engineer (Azure) Job Type: Contract Contract Duration: 6 Months Pay Rate/Salary: CAD $75-80/hr (Incorporated) Location: Downtown Toronto, ON (Hybrid - 3 Days Onsite) What You'll Be Doing Design, develop, and maintain scalable data pipelines within Azure cloud environments. Build and optimize ETL/ELT processes using Azure Synapse Analytics, Azure Data Factory, and Azure Data Lake. Develop data transformation solutions using Mapping Data Flows, T-SQL, PySpark, and Python. Design and maintain enterprise data warehouse and data storage solutions. Build and maintain integrations using REST APIs, Azure Function Apps, Logic Apps, and Event Hub. Support data ingestion, transformation, cleansing, quality validation, and delivery across multiple data platforms. Collaborate with business stakeholders to gather requirements and translate them into scalable data solutions. Create and maintain technical documentation, standards, and development processes. Troubleshoot and resolve data-related issues across development, test, UAT, and production environments. Contribute to cloud data strategy, platform modernization, and continuous improvement initiatives. What You'll Need to Succeed 3+ years of Data Engineering experience with Microsoft Azure technologies. Strong hands-on experience with Azure Data Factory (ADF), Azure Synapse Analytics, Azure Data Lake Storage (ADLS), Azure SQL Database, Azure Function Apps, Logic Apps, and Event Hub. Proficiency in T-SQL, Python, and PySpark. Experience building and supporting enterprise data warehouse solutions. Strong understanding of data modeling and data warehousing principles. Experience working with structured, semi-structured, and unstructured data. Experience developing REST API integrations and data transformation pipelines. Strong troubleshooting, analytical, and problem-solving skills. Excellent communication and stakeholder management capabilities. Nice to Have Microsoft Certified: Azure Data Engineer Associate, Azure Solutions Architect Expert, or Fabric Analytics Engineer Associate. Experience with Microsoft Fabric, Lakehouse, and Warehouse solutions. Experience with DevOps, CI/CD pipelines, and automated deployment processes. Experience implementing data quality controls, validation frameworks, and confidence scoring. Understanding of Medallion Architecture (Bronze, Silver, Gold layers). Experience working within financial services environments. Experience with Agile/Waterfall methodologies and tools such as Jira and Confluence. What You'll Get in Return You will have the opportunity to work on modern Azure cloud and data transformation initiatives within a collaborative team environment. The role offers exposure to enterprise-scale data platforms, cloud technologies, and the potential to contribute to long-term data modernization programs. What You Need to Do Now If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now. If this job isn't quite right for you, but you are looking for a new position, please contact us for a confidential discussion on your career. This posting is for an existing vacancy with the organization. AI may be used to screen, assess or select applicants for the position.

What you’ll do

Requirements

Requires at least three years of data engineering experience with Azure, hands-on expertise in Azure data services, and proficiency in T-SQL, Python, and PySpark. Candidates should have experience with enterprise data warehousing, data modeling, varied data types, REST API integrations, troubleshooting, and stakeholder communication.