Data Solution Automation Engineer

Responsibilities:

QA Strategy and Planning:

• Define QA strategy for a hybrid ETL stack involving Informatica and dbt for data transformation and modeling.
• Analyze Source-to-Target Mapping (STTM) documents, business rules, and dbt model definitions to determine test scope.
• Plan and manage test phases across Program Increments (PIs) or releases including unit testing, system testing, integration testing, and UAT support.

• Review and validate Informatica mappings, workflows, sessions, and parameter files.
• Validate data extraction from flat files, RDBMS, and mainframes.
• Verify transformation logic (joins, lookups, aggregations, filters) and load strategies to staging/ODS layers.
• Use SQL and data comparison tools for reconciliation and validation.
• Monitor job execution using Informatica Monitor and workflow logs.

• Validate dbt models, test logic, and YAML metadata.
• Test SQL logic for business rule accuracy and performance.
• Execute dbt test suites and troubleshoot test failures.
• Collaborate with analytics engineers to verify model materialization strategies and source freshness logic.
• Review compiled SQL for accuracy in transformations.

• Conduct full and sample-based validation across source staging ODS analytics layers.
• Write complex SQL to compare record counts, aggregates, and field-level values.
• Validate PII masking and data obfuscation where applicable.

• Build and maintain reusable SQL test automation scripts.
• Integrate QA checks into CI/CD pipelines using GitHub Actions.
• Monitor and validate Informatica batch schedules and dbt Cloud jobs.
• Contribute to automated QA dashboards and test reporting tools.

• Log and track defects in JIRA by layer (Informatica/dbt) and severity.
• Lead daily defect triage meetings with engineering teams.
• Provide detailed test execution and coverage reports by data domain.

• Collaborate with data engineers, analytics engineers, modelers, and product owners.
• Coordinate test data provisioning and masking with data stewards.
• Participate in Agile ceremonies including sprint planning, retrospectives, and PI Planning.
• Represent QA in system demos and status updates.

• Hands-on experience with Informatica PowerCenter and dbt.
• Strong SQL skills and experience in data reconciliation across multi-layered data pipelines.
• Familiarity with CI/CD pipelines, GitHub Actions, and QA automation.
• Experience working in Agile/Scrum or SAFe environments.
• Experience with JIRA for defect and project tracking.
• Excellent collaboration, communication, and documentation skills.

• Bachelor's degree in Computer Science, Information Systems, or a related field.
• 5+ years of experience in data QA, ETL testing, or data engineering QA roles preferred.