Cloud Data Engineer Location: Toronto, ON Work Model: Hybrid Employment Type: Full-Time Permanent (FTE) Job Summary We are seeking an experienced Cloud Data Engineer to design, develop, and maintain scalable cloud-based data platforms and pipelines.

The ideal candidate will have strong experience in cloud data engineering, ETL/ELT, data lakes, data warehouses, real-time and batch processing , and cloud-native data services across AWS, Azure, or Google Cloud.

Key Responsibilities Design, develop, and maintain scalable batch and real-time data pipelines .

Build, implement, and manage cloud-based data platforms using AWS, Microsoft Azure, or Google Cloud Platform (GCP) .

Develop robust ETL/ELT processes to extract, transform, and load data from multiple structured and unstructured sources.

Design and optimize data lakes, data warehouses, and data marts .

Implement cloud-native data integration solutions using modern data engineering and big data technologies.

Ensure data quality, integrity, security, privacy, and compliance across enterprise data platforms.

Monitor, troubleshoot, and optimize data pipelines to ensure reliability and performance.

Investigate and resolve production data issues and pipeline failures.

Collaborate with Business Analysts, Data Scientists, Data Architects, Application Developers, and business stakeholders to understand and implement data requirements.

Optimize data storage, processing, and compute resources for performance and cost efficiency .

Implement CI/CD, automation, and Infrastructure as Code (IaC) practices for cloud data platforms.

Manage metadata, data lineage, data cataloging, and data governance processes.

Develop solutions that support reporting, analytics, AI/ML,



and Business Intelligence initiatives.

Contribute to cloud data architecture, modernization, and continuous improvement initiatives.

Required Skills & Experience Strong hands-on experience in Cloud Data Engineering .

Experience building and managing data solutions on one or more major cloud platforms: AWS Microsoft Azure Google Cloud Platform (GCP) Strong experience with ETL/ELT development and data integration .

Experience designing and implementing data lakes, data warehouses, and data marts .

Hands-on experience developing batch and real-time/streaming data pipelines .

Robust knowledge of data modeling, data processing, and data engineering best practices.

Experience with cloud-native data services and big data technologies .

Experience with data quality, data validation, security, and governance.

Strong troubleshooting and performance optimization skills.

Experience with CI/CD and Infrastructure as Code (IaC) .

Proficiency in SQL and experience with at least one programming language such as Python, Java, or Scala .

Preferred Qualifications Experience with distributed data processing technologies such as Apache Spark, Kafka, or similar platforms .

Experience with cloud data warehouse technologies such as Snowflake, Databricks, Amazon Redshift, Azure Synapse, or Big

Query .

Experience with data orchestration tools such as Apache Airflow, Azure Data Factory, AWS Glue, or similar technologies .

Experience with Terraform, Cloud

Formation, or ARM/Bicep for Infrastructure as Code.

Knowledge of data cataloging, metadata management, data lineage, and enterprise data governance .

Experience supporting AI/ML and advanced analytics use cases.

Relevant AWS, Azure, or Google Cloud certifications are an asset.

📌 Cloud Data Engineer || Toronto, ON || Fulltime FTE
🏢 AceStack
📍 Toronto