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Added 9 mins ago
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Apptoza Inc.

AWS Data Engineer

Toronto, ON, Canada

Job type: Contract
Apply by: Oct 25, 2026
Experience: 8+ years of strong Data Engineering experience.
Posting language: English
Posted: Sep 25, 2026

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Original job description

Role: AWS Data Engineer

Location: Toronto, ON – Hybrid

Contract Role

Job Summary

Key Responsibilities

Design and develop scalable data pipelines and ETL/ELT processes using AWS services.
Develop complex and optimized SQL queries for data extraction, transformation, and analysis.
Build and maintain data solutions using AWS Glue, S3, Lambda, Athena, Redshift, and EMR.
Develop data transformation workflows using Python/PySpark.
Perform data integration from multiple sources into AWS data platforms.
Implement data quality, validation, transformation, and reconciliation processes.
Optimize data pipelines and SQL queries for performance and cost efficiency.
Work with business and analytics teams to understand data requirements.
Troubleshoot data pipeline failures and resolve data-related issues.
Implement automated testing and monitoring for data pipelines.
Follow data governance, security, and compliance best practices.

Required Skills

8+ years of strong Data Engineering experience.
Strong hands-on experience with AWS Cloud data services.
Excellent SQL skills, including complex queries, joins, CTEs, window functions, and query optimization.
Strong experience with AWS Glue and Amazon S3.
Experience with Amazon Redshift and/or Athena.
Strong Python and/or PySpark experience.
Experience developing ETL/ELT pipelines.
Experience with data warehousing and data modeling.
Strong understanding of batch and real-time data processing.
Experience with Git and CI/CD for data engineering projects.

Preferred Skills

AWS Lambda
Amazon EMR
AWS Step Functions
Amazon Kinesis
Apache Spark
Kafka
Airflow
Data Lake / Data Warehouse architecture
AWS Lake Formation / Glue Data Catalog

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More about this job

Responsibilities

Design, build, and optimize AWS-based data pipelines and ETL/ELT workflows, integrating data from multiple sources and applying data quality, validation, and reconciliation processes. Collaborate with business and analytics teams, troubleshoot pipeline issues, and implement automated testing, monitoring, governance, security, and compliance practices.

Requirements

Requires 8+ years of data engineering experience, strong hands-on AWS data services experience, advanced SQL, and experience with AWS Glue, S3, Redshift and/or Athena, and Python and/or PySpark. Candidates should also have experience with ETL/ELT, data warehousing and modeling, batch and real-time processing, and Git and CI/CD; AWS Lambda, EMR, Step Functions, Kinesis, Spark, Kafka, Airflow, and data lake architecture are preferred.

Skills

AWS Data Services
SQL
AWS Glue
Amazon S3
Amazon Redshift
Amazon Athena
Python
PySpark
ETL/ELT Pipelines
Data Warehousing
Data Modeling
Batch and Real-Time Processing
Git
CI/CD
Data Quality
Data Pipeline Optimization

Visa sponsorship

Not detected in the job text

Keywords

AWS
AWS Glue
Amazon S3
AWS Lambda
Amazon Athena
Amazon Redshift
Amazon EMR
AWS Step Functions
Amazon Kinesis
AWS Lake Formation
AWS Glue Data Catalog
SQL
Python
PySpark
Apache Spark
Kafka
Airflow
ETL/ELT
Data Pipelines
Data Integration
Data Quality
Data Validation
Data Reconciliation
Data Warehousing
Data Modeling
Data Lake Architecture
Batch Processing
Real-Time Processing
Git
CI/CD

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