Quality Engineer – Data Quality & Cloud Analytics Platforms

About the role

Keyrus is looking for a Quality Engineer to own data trust within its Enterprise Data Platform practice. You will design validation frameworks, automate testing and embed quality controls across cloud analytics pipelines, ensuring data products are accurate and reliable for business decisions.

Key responsibilities

• Validate data across ingestion, transformation, integration and processing layers, performing source‑to‑target reconciliation.
• Design, develop and maintain automated and manual testing frameworks integrated into CI/CD pipelines.
• Monitor pipeline execution, identify quality issues and perform root‑cause analysis.
• Collaborate with data engineers, architects and business stakeholders to ensure successful deployment of new data products.
• Manage defects throughout their lifecycle and conduct regression and UAT testing.

Required profile

• 4+ years of experience in data quality engineering, testing or QA for enterprise data platforms.
• Strong analytical mindset with a focus on data accuracy and automation.
• Excellent communication skills, able to explain technical issues to both technical and business audiences.
• Proactive, collaborative attitude and ability to work in fast‑paced, multi‑project environments.

Required skills

• Google Cloud Platform (BigQuery, Dataflow, Cloud Composer, Dataform, Cloud Storage)
• Advanced SQL for large‑scale data validation
• ETL/ELT processes, data modeling and dimensional modeling concepts
• CI/CD practices and integration of quality controls
• Automation scripting (Python or similar)

What we offer

• 100% remote work
• International, multicultural projects
• Access to training programs and continuous professional development
• Opportunities for internal mobility and professional growth
• A collaborative culture focused on innovation and continuous learning