Test Automation QE -3

Realign Llc; Toronto; On-site; CAD 90,000 - 120,000; Full time

Job summary

Realign Llc in Toronto, ON is seeking a Test Automation QE specialized in ETL and API to design and develop automated testing frameworks for data pipelines and cloud-based workloads. You will validate data accuracy, implement SQL validations, Python automation, and contribute to data quality across the stack.

This role requires strong SQL, Python, Unix/Linux scripting, and experience with AWS S3 and Hadoop ecosystems.

Qualifications

• Advanced proficiency in SQL, including complex queries, stored procedures, and data validation.
• Strong Python programming skills for automation and data processing.
• Hands-on experience with Unix/Linux command-line operations and shell scripting.
• Experience with AWS S3 and cloud-based data management.
• Working knowledge of Hadoop and Big Data technologies.
• Experience with ETL testing, data validation, and data quality analysis.
• Familiarity with GitHub, CI/CD practices, and software testing methodologies.

Responsibilities

• Design and develop automated testing frameworks for ETL processes and APIs.
• Write complex SQL queries for data transformation validation, profiling, reconciliation, and root cause analysis.
• Develop Python scripts and utilities for test automation, data validation, and reporting.
• Work with AWS S3, Hadoop ecosystems, and Parquet files to validate and optimize data pipelines.
• Manage code repositories using GitHub and follow CI/CD best practices.
• Apply Quality Engineering principles to identify risks early and implement preventative quality measures.
• Document test results, communicate findings, and provide recommendations for improving data quality.
• Collaborate with both technical and non-technical stakeholders throughout the testing lifecycle.

Skills

SQL

Python

Unix/Linux CLI

Data validation

CI/CD

Tools

AWS S3

Hadoop

Parquet

GitHub

CI/CD tooling

Job description

Job Type: Full Time
Location: Toronto, ON
Work Model: Onsite / 4 Days

Primary Skills: ETL Test Automation, SQL & Python, AWS S3 & Hadoop

Job Description

We are seeking a skilled Test Automation QE - ETL and API professional to design and develop comprehensive automated testing solutions for ETL processes and APIs. The role focuses on ensuring data accuracy, pipeline reliability, and overall system quality through advanced SQL validation, Python automation, cloud data operations, and Quality Engineering practices.

Key Responsibilities

• Design and develop automated testing frameworks for ETL processes and APIs.
• Write complex SQL queries for data transformation validation, profiling, reconciliation, and root cause analysis.
• Develop Python scripts and utilities for test automation, data validation, and reporting.
• Work with AWS S3, Hadoop ecosystems, and Parquet files to validate and optimize data pipelines.
• Manage code repositories using GitHub and follow CI/CD best practices.
• Apply Quality Engineering principles to identify risks early and implement preventative quality measures.
• Document test results, communicate findings, and provide recommendations for improving data quality.
• Collaborate with both technical and non-technical stakeholders throughout the testing lifecycle.

Required Skills & Qualifications

• Advanced proficiency in SQL, including complex queries, stored procedures, and data validation.
• Strong Python programming skills for automation and data processing.
• Hands-on experience with Unix/Linux command-line operations and shell scripting.
• Experience with AWS S3 and cloud-based data management.
• Working knowledge of Hadoop and Big Data technologies.
• Experience with ETL testing, data validation, and data quality analysis.
• Familiarity with GitHub, CI/CD practices, and software testing methodologies.

Preferred Skills

• Experience working with Parquet and large-scale data pipelines.
• Knowledge of API automation and validation.
• Strong analytical, troubleshooting, and communication skills.
• Experience applying QE practices within data engineering environments.