Senior QC Engineer (SQL, ETL Testing)

Location: Bulgaria, Poland, or Romania; remote/office work model

Company

hirify.global delivers software engineering and technology services, including enterprise data platforms for healthcare analytics.

What you will do

• Design and execute testing strategies for enterprise-scale data products covering ingestion, transformation, modeling, governance, quality, and publishing.
• Validate large datasets with complex SQL queries, checking accuracy, completeness, consistency, schema integrity, and metadata quality.
• Test ETL/ELT pipelines and data workflows across GCP services, including BigQuery, Spanner, and Cloud Composer.
• Perform functional, integration, regression, and non-functional testing across the data platform.
• Investigate data quality and pipeline issues using monitoring and logging, collaborating with Data and Platform Engineers on root-cause analysis.
• Maintain test plans, cases, validation scenarios, reports, and data governance quality practices, while improving automation, CI/CD, and platform reliability.

Requirements

• At least 3 years of hands-on Quality Control or Quality Engineering experience, preferably with data-intensive or cloud-based systems.
• Strong experience with GCP data services, especially BigQuery, Spanner, and Cloud Composer.
• Advanced SQL skills, including complex analytical queries and data validation.
• Experience with data quality testing, schema validation, metadata checks, data lineage, ETL/ELT validation, and structured test documentation.
• Understanding of functional, integration, regression, and non-functional testing, with strong analytical and problem-solving skills.
• Proficiency in English and the ability to work from Bulgaria, Poland, or Romania.

Nice to have

• Experience with Google Dataplex, data governance rules, cataloging, metadata management, and data quality policies.
• Familiarity with IBM Netezza and GCP monitoring and logging tools.
• Experience validating AI/ML components, including AI-driven transformations, analysis, and predictions.
• Understanding of data mesh principles and enterprise data platform concepts.
• Interest in expanding technical expertise toward Data Engineering.

Culture & Benefits

• Remote/office work model.
• Collaboration with Data and Platform Engineers in a modern GCP-based data ecosystem.
• Opportunity to work on data products supporting analytics across more than 3,000 healthcare facilities.