Data Quality Engineer

Responsibilities

• Design and implement a data quality framework across Bronze, Silver, and Gold layers
• Build and maintain automated data quality checks within Databricks pipelines
• Own reconciliation between source systems and Databricks layers
• Validate identity resolution outputs in the Silver layer
• Perform end-to-end pipeline testing from ingestion to Gold layer
• Partner with Data Engineers to define acceptance criteria for pipeline deliverables
• Support UAT with client business stakeholders
• Document QA processes, test results, and data quality findings
• Monitor pipeline health post-deployment and triage incidents

Requirements

• 3+ years of experience in Data Engineering or Data Quality roles
• Experience with Azure-based data platforms and Databricks
• Strong understanding of data quality frameworks and testing methodologies
• Experience validating ETL/ELT processes and layered architectures
• Strong SQL skills for analyzing large datasets
• Experience implementing automated data validation and reconciliation
• Familiarity with data pipeline monitoring and alerting
• Advanced English proficiency

Benefits

• Certifications in AWS, Databricks, and Snowflake
• Access to AI learning paths and Udemy Business
• English lessons
• Travel opportunities for industry conferences
• Mentorship and career development plans
• Company-provided equipment
• Flexible working options

About the Company

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