Contract Cloud Data Engineer (AWS/Azure)

Job Title: Senior - Contract Cloud Data Engineer (AWS/Azure)
Type: Contract per hour
Location: Toronto
Environment: Hybrid - mostly remote - must be able to onsite - downtown Toronto

We have been engaged to find a Senior Cloud Data Engineer with a passion for building scalable and optimized cloud data solutions.

Overview:
We are seeking an experienced Cloud Data Engineer with expertise in AWS and Azure to design, build, and optimize scalable cloud-based data solutions. The ideal candidate will have hands-on experience with cloud-native data services, ETL pipelines, and big data processing, ensuring efficient and secure data storage, transformation, and accessibility. This contract role requires strong analytical skills, the ability to work independently, and a deep understanding of data engineering best practices in the cloud.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes on AWS and Azure.
  
• Build and optimize data lakes, data warehouses, and cloud-native storage solutions (e.g., S3, ADLS, Snowflake, Redshift, Synapse).
  
• Implement data modeling, partitioning, and indexing strategies to ensure optimal performance.
  
• Develop and maintain CI/CD pipelines for data engineering workflows.
  
• Work with structured and unstructured data using Spark, Databricks, or Synapse Analytics.
  
• Implement and enforce data governance, security, and compliance best practices.
  
• Optimize query performance and cost efficiency for cloud data platforms.
  
• Work closely with data scientists, analysts, and DevOps teams to support business needs.
  
• Troubleshoot data ingestion, transformation, and performance issues.
  
• Document technical solutions, best practices, and operational procedures.
  

Requirements

Required Skills & Experience:

• 8+ years of experience in data engineering with a focus on cloud-based solutions (AWS and Azure).
  
• Hands-on experience with cloud data services such as:
  
• AWS: S3, Glue, Redshift, Amazon EMR (Elastic MapReduce),Lambda, Kinesis, Step Functions.
  
• Azure: ADLS, Synapse Analytics, Data Factory, Event Hub, Cosmos DB.
  
• Proficiency in SQL, Python, and/or Scala for data processing and transformations.
  
• Experience with ETL/ELT frameworks and tools such as Apache Spark, Databricks, Airflow, or Data Build Tool (dbt)
  
• Strong understanding of data modeling, schema design, and database performance tuning.
  
• Experience with IaC tools like Terraform, CloudFormation, or Bicep.
  
• Knowledge of data governance, security best practices, and compliance frameworks
  
• Familiarity with DevOps & CI/CD pipelines for automating deployments.
  
• Strong analytical and problem-solving skills.
  
• Excellent communication skills and ability to work with cross-functional teams.
  

Nice-to-Have Skills:

Knowledge of machine learning pipelines and MLOps.
Experience working with Kafka, Snowflake, BigQuery, or Hadoop ecosystems.
Certifications in AWS Certified Data Analytics, Azure Data Engineer Associate, or similar.