Data Quality Analyst (Automation)

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

About the Opportunity

A leading financial services organization is building out a new Enterprise Data Warehouse QA function and is seeking a Data Quality Analyst (Automation) to help establish testing standards, automation frameworks, and data quality processes across the organization.

This is an opportunity to join a growing team at the ground level and play a key role in shaping how data quality is measured, validated, and governed. The ideal candidate combines deep SQL expertise, data warehouse testing experience, and automation skills with the ability to influence stakeholders and mentor future team members.

What You'll Do

• Validate data throughout the ETL/ELT lifecycle, from ingestion through transformation and reporting.
• Perform source-to-target validation, reconciliation, and data migration testing.
• Develop automated data quality checks and testing frameworks using SQL and scripting languages.
• Create complex SQL queries to identify data anomalies, investigate defects, and validate business rules.
• Analyze large data sets to ensure completeness, accuracy, and integrity.
• Partner with Data Engineering, BI, Product, and business stakeholders to resolve data issues.
• Build repeatable processes, QA standards, and governance practices for a growing data warehouse organization.
• Review testing results, communicate risks, and provide release readiness recommendations.
• Mentor junior team members and help define future QA processes and best practices.

Required Qualifications

• 4+ years of experience in Data QA, Data Quality, Data Validation, Data Warehouse Testing, or similar.
• Advanced SQL experience, including:
• Window functions
• Aggregations
• Exception reporting
• Experience validating ETL/ELT pipelines, data transformations, ingestion processes, and migrations.
• Strong understanding of data quality testing and warehouse validation methodologies.
• Experience working with large-volume enterprise datasets.
• Strong communication and stakeholder management skills.
• Experience working within Enterprise Data Warehouse environments.

Preferred Qualifications

• Snowflake
• Informatica Data Quality (IDQ) or IICS
• CDC (Change Data Capture) testing and validation
• Financial services, mortgage, banking, or healthcare industry experience
• Jira and qTest
• Power BI and data quality metrics reporting
• Experience establishing QA standards and processes
• Experience mentoring analysts or leading QA initiatives

Ideal Background

This role is best suited for professionals with experience as:

• Data Quality Analyst
• Data Warehouse QA Analyst
• Data Validation Analyst
• Data Test Automation Engineer

If you're passionate about data quality, enjoy solving complex reconciliation challenges, and want to help build a best-in-class data warehouse QA practice, we'd love to connect.