Data Quality Engineer: Azure & Databricks Pipelines

Blend360; Santiago; Hybrid; CLP 55,504,000 - 83,256,000; Full time

Benefits offered by this job

AWS Certifications

Databricks Certification

Snowflake Certifications

Udemy Business access

English lessons

Travel opportunities

Mentorship programs

Company-provided equipment

Job summary

Blend360 is seeking a Data Quality Engineer to ensure data quality, reliability, and consistency across modern data platforms. You will validate data pipelines, implement automated quality checks, and collaborate closely with Data Engineering and business teams to guarantee production-ready data assets.

The role requires 3+ years in Data Engineering or Data Quality, strong SQL, and experience with Azure Databricks.

Qualifications

• Experience with Azure-based data platforms, including Databricks.
• Strong understanding of data quality frameworks and testing methodologies for data pipelines.
• Experience validating ETL/ELT processes and working with layered architectures (Bronze, Silver, Gold).
• Strong SQL skills and experience analyzing large datasets.
• Experience implementing automated data validation and reconciliation processes.
• Familiarity with data pipeline monitoring, alerting, and troubleshooting.
• Ability to collaborate with Data Engineers and business stakeholders.
• Strong analytical thinking and attention to detail.
• Experience documenting QA processes and results in a structured manner.

Responsibilities

• 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 data flows correctly from ingestion through to the Gold layer and that downstream reporting outputs reflect accurate data.
• Partner with Data Engineers to define acceptance criteria for each sprint’s pipeline and data model deliverables before they are promoted to production.
• Support UAT with client business stakeholders - helping them validate that Gold layer outputs meet their reporting requirements.
• Document all QA processes, test results, and data quality findings in a format that can be handed off to the client team at engagement close.
• Monitor pipeline health post-deployment - investigating and triaging data quality incidents and working with engineers to resolve root causes quickly.

Skills

Azure Databricks

Data quality frameworks

ETL/ELT validation

SQL proficiency

Pipeline monitoring

Stakeholder collaboration

Analytical thinking

Documentation

Data reconciliation

Tools

Azure

Databricks

Job description

Blend360 is seeking a Data Quality Engineer to ensure data quality, reliability, and consistency across modern data platforms. You will validate data pipelines, implement automated quality checks, and collaborate closely with Data Engineering and business teams to guarantee production-ready data assets.

The role requires 3+ years in Data Engineering or Data Quality, strong SQL, and experience with Azure Databricks.