Data Engineer - Senior - 989
Summary
Senior Data Engineer builds and maintains scalable Azure-based data pipelines and architectures, integrating diverse sources and enabling analytics and ML use cases.
About Us
A Canadian technology and workforce solutions company headquartered in Vaughan, Ontario. The company helps businesses, enterprises, and public-sector organizations modernize their operations through secure digital transformation, custom software development, staffing, recruitment, payroll, and workforce management solutions.
Job Description
Title
Data Engineer - Senior
Duration
2026-09-01 to 2027-08-31 (6 Months possible extension)
Location
Edmonton, AB (Remote)
Duties
- Collaborate with business stakeholders and product owners to understand data product objectives, requirements, and success criteria
- Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud-native and hybrid environments.
- Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
- Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance.
- Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts.
- Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases and downstream consumption.
- Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks.
- Design and expose secure data services and APIs using Azure API Management for downstream systems.
- Implement data governance practices, including metadata management, data classification, and lineage tracking.
- Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role-based access controls, encryption, and data masking.
- Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform.
- Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation.
- Leverage AI-assisted tools for code generation, optimization, and review to improve development efficiency and code quality.
- Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.
- Other duties as needed