Cloud Data Engineer - Real-Time Pipelines & Data Lakes

Acestack; Toronto; Hybrid; CAD 90,000 - 140,000; Full time

Job summary

Acestack is seeking a Cloud Data Engineer to design, develop, and maintain scalable cloud-based data platforms and pipelines. You will work across AWS, Azure, and GCP, building ETL/ELT processes, data lakes, warehouses, and data marts for analytics and reporting.

Ideal candidates have hands-on experience with batch and streaming pipelines, data governance, and CI/CD practices. Hybrid work in Toronto, with a focus on performance, cost efficiency, and secure data management.

Qualifications

• Experience across AWS, Azure, or GCP data services.
• Strong ETL/ELT development and data integration expertise.
• Hands-on with batch and real-time data pipelines.
• Experience designing data lakes, warehouses, and marts.

Responsibilities

• Design, develop, and maintain scalable batch and real-time data pipelines.
• Build cloud-based data platforms using AWS, Azure, or GCP.
• Develop ETL/ELT processes to integrate multiple data sources.
• Design data lakes, warehouses, and data marts for analytics.
• Implement data integration with modern big data technologies.
• Ensure data quality, security, and governance across platforms.
• Monitor and optimize pipelines for reliability and performance.
• Troubleshoot production data issues and outages.
• Collaborate with analysts, data scientists, and stakeholders on data requirements.
• Optimize storage, processing, and compute for cost efficiency.
• Implement CI/CD, IaC, and automation for data platforms.
• Maintain metadata, lineage, and data catalogs.

Skills

Cloud Data Engineering

ETL/ELT development

Data lakes, data warehouses

Batch and streaming pipelines

CI/CD and IaC

SQL and Python/Java/Scala

Tools

Apache Airflow

Terraform

CloudFormation

Snowflake/Databricks/BigQuery

Azure/AWS/GCP data services

Job description

Acestack is seeking a Cloud Data Engineer to design, develop, and maintain scalable cloud-based data platforms and pipelines. You will work across AWS, Azure, and GCP, building ETL/ELT processes, data lakes, warehouses, and data marts for analytics and reporting.

Ideal candidates have hands-on experience with batch and streaming pipelines, data governance, and CI/CD practices. Hybrid work in Toronto, with a focus on performance, cost efficiency, and secure data management.