Blendis a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people.

With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence.

The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy.

We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients.

For more information, visit www.blend360.com We are seeking Data Quality Engineer to contribute to our next level of growth and expansion.

What is this position about? We are looking for a Data Quality Engineer with strong experience in Azure and Databricks to ensure data quality, reliability, and consistency across modern data platforms.

This role focuses on validating data pipelines, implementing automated quality checks,



and collaborating closely with Data Engineering and business teams to guarantee accurate and production-ready data assets.

Design and implement a data quality framework across Bronze, Silver, and Gold layers — defining validation rules, threshold tolerances, and alerting standards Build and maintain automated data quality checks within Databricks pipelines — row counts, null checks, referential integrity, schema validation, and business rule assertions Own reconciliation between source systems and Databricks layers — ensuring source data lands accurately and transformations produce expected outputs Validate identity resolution outputs in the Silver layer — reviewing match rates, investigating false positives and false negatives, and ensuring enterprise identifiers are being assigned correctly across source populations Perform end-to-end pipeline testing — validating that dat

📌 Data Quality Engineer (Argentina)
🏢 Blend
📍 Argentina