QA Automation Engineer (Data)

Jobgether; Remote; USD 30,000 - 32,000; Full time

Job summary

A recruitment platform is seeking a QA Automation Engineer (Data) to ensure data quality across large-scale data pipelines in a remote environment. The ideal candidate has 6-10 years of automation experience, strong SQL and Python skills, and is experienced in testing ETL/ELT workflows. This role offers competitive compensation, flexible hours, and a chance to work with cutting-edge analytics platforms. You'll design testing frameworks to enhance data systems that drive analytics and AI initiatives.

Benefits

Competitive annual compensation

Remote-first role with flexible hours

Collaborative environment

Qualifications

• 6–10+ years of QA automation experience in data environments.
• Extensive experience testing cloud-based data workflows.
• Excellent written and verbal communication skills.

Responsibilities

• Design and maintain automated test frameworks for data workflows.
• Validate data accuracy and completeness.
• Automate regression tests and schema validations.

Skills

SQL proficiency

Python for automation scripting

Analytical skills

Problem-solving skills

Experience with ETL/ELT pipelines

Tools

Snowflake

Databricks

ADF

AWS Glue

Airflow

Job description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a QA Automation Engineer (Data) in Germany.

This role offers an exciting opportunity to ensure data quality and reliability across complex, large-scale data pipelines in a fast-paced, analytics-driven environment. You will design, develop, and maintain automated testing frameworks for ETL/ELT workflows, validate data integrity, and implement monitoring for streaming and batch pipelines. Your contributions will directly impact the accuracy, consistency, and performance of mission‑critical data systems. This position combines hands‑on automation, SQL‑based data validation, and collaboration with cross‑functional engineering teams to solve challenging data quality problems. It is ideal for someone passionate about building scalable testing solutions, driving best practices in QA, and working in a remote, flexible, and highly collaborative setting. You will help accelerate the delivery of trustworthy data for analytics and AI initiatives.

Accountabilities

• Design, develop, and maintain automated test frameworks for ETL/ELT and streaming data workflows.
• Build reusable components for Snowflake, Databricks, ADF, Airflow, and other data platforms.
• Automate regression tests, schema validation, data contract checks, and monitoring of data quality.
• Validate data accuracy, completeness, and consistency across ingestion, transformation, and downstream layers.
• Perform root‑cause analysis for data inconsistencies and collaborate with engineers to implement corrective actions.
• Participate in Agile ceremonies, review requirements, estimate tasks, and verify deployment outcomes.
• Document QA best practices and create reusable testing assets to elevate overall data quality standards.

Requirements

• 6–10+ years of QA automation experience in data‑intensive or analytics‑focused environments.
• Strong proficiency in SQL for data validation, profiling, and regression testing.
• Hands‑on experience with Python for automation scripting and data quality frameworks.
• Extensive experience testing ETL/ELT pipelines and cloud‑based data workflows.
• Familiarity with CI/CD pipelines, version control (Git), and automated execution environments.
• Strong analytical, problem‑solving, and troubleshooting skills.
• Excellent written and verbal communication skills.
• Experience with Snowflake and at least one test automation framework; knowledge of Databricks, ADF, AWS Glue, streaming platforms, or orchestration tools is a plus.

Benefits

• Competitive annual compensation: $30,000 – $32,000 USD.
• Remote‑first role with flexible working hours and autonomy.
• Opportunity to design and implement scalable data QA frameworks.
• Exposure to modern cloud‑based analytics platforms and automation tools.
• Collaborative environment with globally distributed engineering teams.
• Contribution to mission‑critical data systems used for analytics and AI innovation.

Why Apply Through Jobgether?

We use an AI‑powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top‑fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Data Privacy Notice

By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre‑contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.