Join our team as a Senior Technical Data Validation Engineer, focusing on Data Warehouse Modernization. This pivotal role involves ensuring the integrity of migrated data during System Integration Testing (SIT). You will be responsible for comprehensive data validation, source-to-target reconciliation, pinpointing data discrepancies, and collaborating with development teams for swift defect resolution.

We seek candidates with proven expertise in DBT, Snowflake, ETL/Data Warehouse principles, SQL-based reconciliation, and legacy Informatica workflows. The ideal professional can independently analyze intricate data issues and provide clear, actionable diagnostics.

Key responsibilities include end-to-end data validation across Informatica and DBT implementations, verifying data completeness, accuracy, and transformations across all data layers. You will execute various validation types, including record counts, aggregates, and incremental loads.

Your role involves analyzing discrepancies, identifying root causes, and meticulously documenting defects with detailed diagnostics to expedite resolution. Furthermore, you will translate Informatica mappings into DBT models, develop and maintain DBT tests, and contribute to the design and optimization of DBT models and Snowflake queries.

This position also entails supporting SIT strategy, reviewing test cases, and ensuring defects are thoroughly documented with root-cause analysis and remediation recommendations. Maintaining validation documentation and evidence is also a crucial aspect of this role.

A minimum of 7 years of experience in Data Warehouse, ETL, Data Engineering, or Data Validation is required, with at least 2 years of hands-on experience with DBT (Core or Cloud). Significant experience in Data Warehouse Migration/Modernization programs and supporting SIT or large-scale data validation initiatives is essential.

Candidates must possess a developer-level understanding of Informatica mappings and workflows, alongside experience with Snowflake and modern cloud data platforms. Strong analytical skills and the ability to comprehend existing ETL logic and requirements documentation are also necessary.

Essential skills include advanced SQL, comprehensive ETL/Data Warehouse testing, source-to-target data validation, proficiency in dbt and Snowflake, data mapping, and defect analysis. Experience with SIT execution support, reconciliation reporting, and business rule validation is also a must-have.