Data QA Engineer - Remote, Flexible Work & 35 Days PTO

Jobgether; Canada; Remote; CAD 90,000 - 120,000; Full time

Benefits offered by this job

35 days holidays

Flexible, location-independent work

Global, multicultural team

Open-source technologies

Autonomy and ownership

Collaborative environment

Job summary

Jobgether is seeking a Data QA Engineer based in Canada to ensure accurate, complete, and reliable data for customers across web data extraction and AI-assisted projects. You will translate requirements into quantifiable QA standards and help prevent defects from reaching production.

You will use Python, SQL, and modern testing tools to assess data quality, create reports, and collaborate with project managers, developers, and clients to improve QA processes.

Qualifications

• At least 5 years of QA or data testing experience.
• Proficient in Python for data validation, with Pandas/Jupyter notebooks preferred.
• Strong SQL skills for data querying in relational databases.
• Experience with web tech: HTML, XPath, JSON, HTTP, CSS.
• Experience testing HTTP/REST APIs and validating responses.

Responsibilities

• Translate customer data extraction needs into testable QA criteria.
• Perform exploratory, manual, and automated testing to ensure data quality.
• Validate datasets against customer specifications and document defects clearly.
• Analyze data quality, completeness, accuracy, and drift using statistics and visuals.
• Prepare quality reports and metrics communicated to teams and customers.
• Identify scope, risks, and untested areas to inform decisions.
• Collaborate with managers, developers, and clients to clarify requirements.
• Contribute to test automation framework improvements.

Skills

QA experience

Python

SQL

Web technologies

APIs testing

Test design

Data quality concepts

Agile

AI/LLM tooling

English communication

Tools

Pandas

Jupyter notebooks

Job description

Jobgether is seeking a Data QA Engineer based in Canada to ensure accurate, complete, and reliable data for customers across web data extraction and AI-assisted projects. You will translate requirements into quantifiable QA standards and help prevent defects from reaching production.

You will use Python, SQL, and modern testing tools to assess data quality, create reports, and collaborate with project managers, developers, and clients to improve QA processes.