IT QA Data Quality Analyst

Summary

Guild Mortgage Company is a mortgage banking firm dedicated to serving homeowners and buyers with affordable home financing. The IT QA Data Quality Analyst performs quality assurance activities for Enterprise Data Warehouse, Data Services, and related data delivery initiatives. The role develops and executes data validation, reconciliation, regression testing, defect analysis, traceability, and release-readiness activities across data platforms and delivery layers.

Responsibilities

• Execute and continuously improve repeatable Data QA approaches for EDW and Data Services initiatives using established risk-based testing, validation standards, quality gates, and release readiness expectations
• Design, develop, document, and perform data quality checks throughout the Enterprise Data Warehouse
• Apply established testing entry, exit, suspension, and completion criteria to assigned data delivery initiatives
• Develop and execute test plans that validate source-to-target mappings, business rules, transformation logic, referential integrity, duplicates, null handling, key relationships, data completeness, and data accuracy
• Validate CDC processing, including inserts, updates, deletes, incremental loads, historical data processing, and reconciliation between source and target systems
• Validate data masking, sensitive data handling, and privacy-related transformation rules with appropriate technical and business stakeholders
• Perform source-to-target reconciliation and data validation across operational systems, Microsoft/Azure data platforms, EDW layers, cloud storage, pipelines, and downstream reporting or analytics products
• Write SQL and other quality-assurance reports to evaluate and analyze data content at platform levels; this does not include business report development
• Work with Data Engineers and BI Engineers to model, calculate, and track data quality results
• Create or maintain BI dashboards that show data quality measures, population metrics, defect trends, testing progress, and release readiness indicators
• Analyze incoming data feeds for completeness, content, timeliness, accuracy, and alignment with data expectations; identify trends across time and other dimensions
• Identify gaps in metadata, reference data, standardization, business rules, and data quality controls
• Create alert mechanisms for system issues, data quality issues, data receipt, completeness, and expected schedule variances
• Partner with Product, Development, Data Engineering, DataOps, BI Engineering, UAT, business stakeholders, and vendors to support certification of data
• Create and maintain requirements traceability that connects requirements, source and target data, test cases, execution results, defects, and test evidence
• Support defect analysis and root cause investigation with clear data evidence, reproduction steps, impacted records, business-rule context, and downstream-impact assessment
• Perform regression testing for code releases, data pipeline changes, EDW enhancements, reporting changes, and other production-impacting data changes
• Identify and implement opportunities to automate repeatable SQL validation, source-to-target reconciliation, data comparison, regression testing, and quality reporting
• Maintain test execution, defect tracking, traceability, and evidence in approved test management and work tracking tools such as qTest, Jira, or equivalent systems
• Communicate test status, data quality findings, unresolved risks, and supporting evidence to help project stakeholders make release decisions
• Perform other duties as assigned

Skills

• * Minimum two years experience with Corporate data management systems in high-compliance contexts required
• * No direct supervisory experience required
• * No certifications or licenses required
• * Knowledge of data quality concepts, including source-to-target mapping, data reconciliation, snowflake/star schema, dimensional modeling, slowly changing dimensions, referential integrity, completeness, correctness, consistency, validity, uniqueness, and timeliness
• * Strong SQL skills, including joins, aggregations, common table expressions, window functions, exception and reconciliation queries, duplicate and null analysis, key validation, and transformation validation
• * Experience validating ETL/ELT pipelines, data ingestion, transformation, movement, warehouse layers, dimensional models, and downstream reporting outputs
• * Experience validating CDC, incremental loads, inserts, updates, deletes, historical processing, and Type 2 slowly changing dimension behavior
• * Experience performing source-to-target validation and reconciliation across source systems, enterprise data warehouses, cloud data platforms, and analytics products
• * Experience validating data masking, sensitive data handling, privacy-related rules, and downstream reporting impacts
• * Basic knowledge of statistical techniques such as the Shewhart method, trend analysis, and other methods used to assess data quality patterns
• * Experience with automated testing, SQL-based validation, data comparison, regression testing, and test data management across multiple workstreams
• * Experience with defect management, defect analysis, root cause investigation, requirements traceability, and audit-ready evidence
• * Experience using Jira and qTest, or equivalent tools, for test planning, execution, defect tracking, traceability, and evidence management
• * Experience implementing data quality metrics, dashboards, release readiness reporting, and audit evidence
• * Excellent verbal and written communication skills; ability to communicate technical findings and risks clearly
• * Ability to think critically, evaluate facts and data, draw conclusions, determine downstream impact, assess risk, solve technical problems, and think abstractly
• * Ability to create clear, concise, and detail-oriented test plans, test cases, test evidence, defect documentation, and release readiness summaries
• * Excellent verbal and written communication skills required
• * Highly organized and detail-oriented; ability to work in a fast-paced, metrics-driven environment required
• * Proficiency in Microsoft Office Suite, Word, Excel, Wiki, collaborative cloud-based programs, and third-party software applications required
• * Ability to accurately interpret sounds and associated meanings at a volume consistent with interpersonal conversation
• * Regularly required to accurately perceive, distinguish and interpret information received visually and through audio; e.g., words, numbers and other data broadcasted aloud/viewed on a screen, as well as print and other media
• * Travel: 5%
• * Work is primarily performed during the business week, Monday - Friday
• * Bachelors Degree directly related to the position or equivalent, preferred
• * Experience in Data QA, Data Warehouse QA, ETL/ELT testing, BI testing, or data quality validation preferred
• * Knowledge of Microsoft and Azure data platforms preferred, including Azure SQL, Azure Data Lake Storage, Azure Data Factory or Synapse pipelines, Microsoft Fabric, Power BI, and Microsoft Purview where applicable; knowledge of Snowflake and cloud-based data warehouse concepts is also preferred
• * Experience with cloud data platforms and storage technologies, including Azure Data Lake Storage and Microsoft data services preferred; AWS S3 or similar object storage experience is a plus. Knowledge of Parquet, Avro, and other structured or semi-structured data formats
• * Knowledge of Informatica Data Quality and IICS, including data quality checks for correctness, completeness, consistency, validity, and uniqueness

Qualifications

Must Haves

• * Minimum two years experience with Corporate data management systems in high-compliance contexts required
• * No direct supervisory experience required
• * No certifications or licenses required
• * Knowledge of data quality concepts, including source-to-target mapping, data reconciliation, snowflake/star schema, dimensional modeling, slowly changing dimensions, referential integrity, completeness, correctness, consistency, validity, uniqueness, and timeliness
• * Strong SQL skills, including joins, aggregations, common table expressions, window functions, exception and reconciliation queries, duplicate and null analysis, key validation, and transformation validation
• * Experience validating ETL/ELT pipelines, data ingestion, transformation, movement, warehouse layers, dimensional models, and downstream reporting outputs
• * Experience validating CDC, incremental loads, inserts, updates, deletes, historical processing, and Type 2 slowly changing dimension behavior
• * Experience performing source-to-target validation and reconciliation across source systems, enterprise data warehouses, cloud data platforms, and analytics products
• * Experience validating data masking, sensitive data handling, privacy-related rules, and downstream reporting impacts
• * Basic knowledge of statistical techniques such as the Shewhart method, trend analysis, and other methods used to assess data quality patterns
• * Experience with automated testing, SQL-based validation, data comparison, regression testing, and test data management across multiple workstreams
• * Experience with defect management, defect analysis, root cause investigation, requirements traceability, and audit-ready evidence
• * Experience using Jira and qTest, or equivalent tools, for test planning, execution, defect tracking, traceability, and evidence management
• * Experience implementing data quality metrics, dashboards, release readiness reporting, and audit evidence
• * Excellent verbal and written communication skills; ability to communicate technical findings and risks clearly
• * Ability to think critically, evaluate facts and data, draw conclusions, determine downstream impact, assess risk, solve technical problems, and think abstractly
• * Ability to create clear, concise, and detail-oriented test plans, test cases, test evidence, defect documentation, and release readiness summaries
• * Excellent verbal and written communication skills required
• * Highly organized and detail-oriented; ability to work in a fast-paced, metrics-driven environment required
• * Proficiency in Microsoft Office Suite, Word, Excel, Wiki, collaborative cloud-based programs, and third-party software applications required
• * Ability to accurately interpret sounds and associated meanings at a volume consistent with interpersonal conversation
• * Regularly required to accurately perceive, distinguish and interpret information received visually and through audio; e.g., words, numbers and other data broadcasted aloud/viewed on a screen, as well as print and other media
• * Travel: 5%
• * Work is primarily performed during the business week, Monday - Friday

Nice to Haves

• * Bachelors Degree directly related to the position or equivalent, preferred
• * Experience in Data QA, Data Warehouse QA, ETL/ELT testing, BI testing, or data quality validation preferred
• * Knowledge of Microsoft and Azure data platforms preferred, including Azure SQL, Azure Data Lake Storage, Azure Data Factory or Synapse pipelines, Microsoft Fabric, Power BI, and Microsoft Purview where applicable; knowledge of Snowflake and cloud-based data warehouse concepts is also preferred
• * Experience with cloud data platforms and storage technologies, including Azure Data Lake Storage and Microsoft data services preferred; AWS S3 or similar object storage experience is a plus. Knowledge of Parquet, Avro, and other structured or semi-structured data formats
• * Knowledge of Informatica Data Quality and IICS, including data quality checks for correctness, completeness, consistency, validity, and uniqueness

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Life insurance
• AD&D insurance
• LTD insurance
• 401(k) with employer match