Data Quality Automation Analyst for Data Warehouses

Insight Global; United States; On-site; USD 90,000 - 130,000; Full time

Job summary

Insight Global is partnering with a leading financial services organization to build a new Enterprise Data Warehouse QA function. The Data Quality Analyst (Automation) will help establish testing standards, automation frameworks, and data quality processes across the organization.

The role requires validating data through the ETL/ELT lifecycle, developing automated checks, mentoring juniors, and aligning QA with stakeholders to ensure governed, accurate data for reporting.

Qualifications

• 4+ years in Data QA/warehouse testing or similar.
• Strong SQL with window functions and aggregations.
• Experience validating ETL/ELT pipelines and migrations.
• Knowledge of data quality testing methodologies and governance.
• Experience with large enterprise data sets and stakeholder management.

Responsibilities

• Validate data across ETL/ELT lifecycle from ingestion to reporting.
• Perform source-to-target validation and data migration testing.
• Develop automated data quality checks and testing frameworks.
• Create complex SQL queries to identify data anomalies and verify rules.
• Analyze large data sets for completeness and accuracy.
• Partner with Data Engineering, BI, Product, and business teams to resolve issues.
• Build QA standards and governance for a growing data warehouse.
• Review results, communicate risks, and assess release readiness.
• Mentor junior team members and help define QA processes.

Skills

Advanced SQL

Window functions

ETL testing

Data quality

DW testing

Data reconciliation

Stakeholder comm

Tools

Snowflake

Informatica IDQ

qTest

Jira

Power BI

IICS

Job description

Insight Global is partnering with a leading financial services organization to build a new Enterprise Data Warehouse QA function. The Data Quality Analyst (Automation) will help establish testing standards, automation frameworks, and data quality processes across the organization.

The role requires validating data through the ETL/ELT lifecycle, developing automated checks, mentoring juniors, and aligning QA with stakeholders to ensure governed, accurate data for reporting.