Join our team as a Senior Technical Data Validation Engineer, a pivotal role in our Data Warehouse Modernization Program. You will be instrumental during System Integration Testing (SIT), focusing on validating migrated data pipelines, ensuring source-to-target reconciliation, and pinpointing the root causes of data discrepancies. Your collaboration with development teams will be key to accelerating defect resolution.

The ideal candidate brings extensive expertise in DBT, Snowflake, ETL/Data Warehouse concepts, and SQL-based reconciliation. A strong understanding of legacy Informatica workflows is also essential, along with the capability to independently analyze complex data issues and provide actionable diagnostic insights.

Your core responsibilities include performing end-to-end data validation across Informatica and DBT implementations, verifying data completeness, accuracy, transformations, and business rules. You will execute various validation types such as record count, aggregate, reconciliation, SCD, and incremental loads. Analyzing discrepancies, identifying root causes, and preparing detailed defect diagnostics will be crucial.

Additionally, you'll translate Informatica mappings into DBT models, develop and maintain DBT tests, and design data layers using DBT best practices. You will also contribute to performance analysis and optimization of DBT models and Snowflake queries, while supporting deployment validation and migration activities. Your role extends to contributing to SIT strategy, reviewing test cases, and maintaining comprehensive validation documentation.

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

A developer-level understanding of Informatica mappings and workflows, coupled with experience in Snowflake and modern cloud data platforms, is necessary. Strong advanced SQL, ETL/Data Warehouse testing, source-to-target data validation, and defect analysis skills are mandatory. Experience with Databricks and CI/CD tools like Azure DevOps is strongly preferred.