About The Role
In this role, you will ensure the quality and reliability of enterprise-scale Data Products and platform capabilities that enable analytics across more than 3,000 healthcare facilities. Working within a modern GCP-based data ecosystem, you will validate complex data pipelines, transformations, and governance processes while collaborating with Data and Platform Engineers. The role also offers an opportunity to expand your expertise toward Data Engineering.
Responsibilities
- Design and execute comprehensive testing strategies for enterprise-scale Data Products, covering data ingestion, transformation, modeling, quality, governance, and publishing
- Validate large-scale datasets using complex SQL queries, ensuring data accuracy, completeness, consistency, schema integrity, and metadata quality
- Test data pipelines and ETL/ELT workflows across GCP services, including BigQuery, Spanner, and Cloud Composer
- Perform functional, integration, regression, and non-functional testing to ensure reliable data processing across the platform
- Investigate data quality and pipeline issues using monitoring and logging capabilities, collaborating with Data and Platform Engineers to identify root causes
- Build and maintain structured test documentation, including test plans, test cases, validation scenarios, and test reports
- Contribute to data governance and quality practices, including validation of metadata, lineage, cataloging, and data quality rules
- Validate AI/ML-enabled data capabilities, including AI-driven transformations, analysis, and predictions, with a focus on data quality, accuracy, and logic correctness
- Contribute to continuous improvements in test automation, CI/CD, quality engineering practices, and overall platform reliability
Requirements
- At least 3 years of hands-on experience in Quality Control or Quality Engineering, preferably with data-intensive or large-scale cloud-based systems
- Strong hands-on experience with GCP data services, particularly BigQuery, Spanner, and Cloud Composer
- Advanced SQL skills with experience writing complex analytical queries, preferably using BigQuery SQL
- Strong experience in data validation and data quality testing, including schema validation, metadata checks, data lineage, and functional validation
- Solid understanding of functional, integration, regression, and non-functional testing approaches
- Experience creating and maintaining structured test documentation, including test plans, test cases, and test reports
- Experience validating data pipelines and ETL/ELT processes
- Strong analytical and problem-solving skills with the ability to investigate complex data quality issues
- Strong communication skills, a proactive and consultative mindset, and proficiency in English
- Interest in expanding technical expertise toward Data Engineering
- Experience with Google Dataplex, including data governance rules, cataloging, metadata management, and data quality policies (would be a plus)
- Familiarity with IBM Netezza (would be a plus)
- Experience with GCP monitoring and logging tools, including Cloud Logging, Cloud Monitoring, and Error Reporting (would be a plus)
- Experience validating AI/ML components integrated into data platforms, including AI-driven transformations, analysis, and predictions (would be a plus)
- Understanding of data mesh principles and enterprise data platform concepts (would be a plus)
SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.