Data Quality Analyst

AI AXISS INC; San Antonio (TX); On-site; USD 90,000 - 130,000; Full time

Job summary

AI AXISS INC is seeking a data quality engineer to lead efforts to implement new Data Quality standards, modernize ETL pipelines with reusable engineering patterns in a shift-left approach.

The role focuses on embedding automated DQ checks, CI/CD integration, and monitoring and reporting of DQ results to drive governance and reliability across data platforms.

Qualifications

• Strong ETL/ELT and data engineering experience with Datastage, DBT, Informatica and Snowflake.
• Hands-on Data Quality engineering experience.
• Experience embedding automated DQ checks into pipelines.
• Strong CI/CD and automated testing knowledge.
• Understanding of shift-left/inline DQ architecture.
• Technical leadership and ability to drive adoption across engineering teams.

Responsibilities

• Implement DQ checks across priority ETL pipelines.
• Incorporate completeness, validity, accuracy, consistency, uniqueness, and reconciliation checks.
• Determine appropriate DQ checkpoints throughout the pipeline.
• Integrate DQ validation into automated pipeline testing and CI/CD processes.
• Establish quality gates and thresholds for pipeline promotion.
• Automate execution and reporting of DQ tests.
• Implement standardized approaches for handling DQ failures.
• Define reject, quarantine, warning, and pipeline-stop patterns.
• Enable automated alerting and issue routing.
• Implement monitoring of DQ results within ETL pipelines.
• Provide visibility into DQ failures, trends, and recurring issues.
• Capture DQ results and metadata for downstream reporting and governance.

Skills

ETL/ELT

Data quality

CI/CD

Automated testing

Leadership

Shift-left

Tools

Datastage

DBT

Informatica

Snowflake

Job description

Lead efforts to implement new Data Quality standards, emphasizing on modernizing existing ETL pipelines with reusable engineering patterns for implementing Data quality in a "shift left" approach.

Required Skills

• Strong ETL/ELT and data engineering experience (Datastage, DBT, Informatica, Snowflake)
• Hands‑on Data Quality engineering experience
• Experience embedding automated DQ checks into pipelines
• Strong CI/CD and automated testing knowledge
• Understanding of shift-left/inline DQ architecture
• Technical leadership and ability to drive adoption across engineering teams

DQ-Enabled ETL Pipelines

• Implement DQ checks across priority ETL pipelines
• Incorporate completeness, validity, accuracy, consistency, uniqueness, and reconciliation checks
• Determine appropriate DQ checkpoints throughout the pipeline

Automated DQ Testing & CI/CD Integration

• Integrate DQ validation into automated pipeline testing and CI/CD processes
• Establish quality gates and thresholds for pipeline promotion
• Automate execution and reporting of DQ tests
• Implement standardized approaches for handling DQ failures
• Define reject, quarantine, warning, and pipeline‑stop patterns
• Enable automated alerting and issue routing

DQ Monitoring & Reporting

• Implement monitoring of DQ results within ETL pipelines
• Provide visibility into DQ failures, trends, and recurring issues
• Capture DQ results and metadata for downstream reporting and governance