Big Data Test Manager - Enterprise Data Lakehouse

Wer wir sind

EPAM Systems ist ein führender Anbieter von digitaler Ingenieurskunst, Cloud- und KI-gestützten Transformationsdiensten sowie ein wichtiger Partner für Unternehmens- und Erfahrungskonsultationen für globale Unternehmen und Startups.

Responsibilities

• Lead the end-to-end test strategy for our client’s enterprise-level Data Lakehouse program, ensuring the validation of complex ETL/ELT pipelines, transformations and downstream banking data products
• Drive and design test automation initiatives specifically tailored for the client’s data validation, data quality reconciliation and pipeline execution within Kubernetes-based CI/CD environments
• Ensure robust test data management and coordinate integration testing across the client's 70+ connected consuming applications and globally distributed environments
• Oversee testing for two key areas, Data pipelines and banking domain data products and Platform-as-a-Service capabilities for the Data Lakehouse
• Establish test governance, entry/exit criteria, defect management processes and quality standards across multiple workstreams
• Collaborate with data engineers, platform teams, product owners and application owners to resolve cross-functional issues and influence test coverage alignment
• Drive production readiness and release validation activities for platform and data ecosystem changes

Requirements

• Proven experience managing testing within large-scale enterprise data platforms, such as Data Lakes, Data Lakehouses or modern Data Warehouses (ideally in highly regulated environments like Banking)
• Strong understanding of data testing vs. traditional application testing, with hands-on expertise in data quality validation, reconciliation, schema drift and data lineage
• Hands-on experience in test automation for data pipelines, APIs and data platform services using industry-standard tools and scripting frameworks
• Experience coordinating integration and regression testing across distributed, multi-application environments without direct ownership of downstream systems
• Familiarity with modern data platform infrastructure and operations, including Kubernetes, S3 Object Storage and containerized DevOps pipelines
• Experience implementing and scaling test automation frameworks designed specifically for high-volume data validation and pipeline testing (as opposed to standard UI-centric automation)
• Excellent stakeholder management and communication skills to lead testing in global, regulated environments
• Higher education in Computer Science, Engineering or related field preferred
• English proficiency required; German language skills are an advantage

Fähigkeiten

Test & QADockerICTKubernetes

Gehaltsspanne

Auf Anfrage

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