Cloud Data Engineer
Design and maintain scalable cloud-based data pipelines and platforms for batch and real-time processing. Ensure data quality, security, and governance while supporting AI/ML and business intelligence initiatives.
- On-site
- Toronto, ON
- Posted Aug 27, 2026
- Apply by Sep 26, 2026
- 1 position
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Job summary
"• Design, develop, and maintain scalable data pipelines for batch and real-time data processing. • Build and manage cloud-based data platforms using AWS, Azure, or Google Cloud. • Develop ETLELT processes to extract, transform, and load data from multiple sources. • Create and optimize data lakes, data warehouses, and data marts. • Ensure data quality, integrity, security, and compliance across data platforms. • Implement data integration solutions using cloud-native services and big data technologies. • Monitor and troubleshoot data pipeline performance and resolve production issues. • Collaborate with business analysts, data scientists, architects, and application teams to understand data requirements. • Optimize data storage and processing for performance and cost efficiency. • Implement automation, CICD, and Infrastructure as Code (IaC) practices for data platforms. • Manage metadata, data lineage, and data governance processes. • Support reporting, analytics, AIML, and business intelligence initiatives by providing reliable data solutions. "
What you’ll do
Design and maintain scalable cloud-based data pipelines and platforms for batch and real-time processing. Ensure data quality, security, and governance while supporting AI/ML and business intelligence initiatives.
Requirements
Requires expertise in cloud platforms like AWS, Azure, or GCP and the ability to implement ETL/ELT processes. Candidates should be proficient in automation, CI/CD, and Infrastructure as Code practices.
Listed skills
- Microsoft AzurePreferred
- SQLPreferred
- CI/CDPreferred
- Amazon Web ServicesPreferred
- Google CloudPreferred
- PythonPreferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Cloud Data Engineering
- AWS
- Azure
- Google Cloud
- ETL/ELT
- Data Lake
- Data Warehouse
- Data Mart
- Big Data Technologies
- CI/CD
- Infrastructure as Code
- Data Governance
- Data Integration
- Python
- SQL
- Data Pipeline Design
Job areas
- Data & Analytics
- Technology
- Engineering
- Software
- Consulting
Additional details
- Minimum experience
- 5+ years
- Apply by
- Sep 26, 2026
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available