> Markdown version of [/jobs/ext/4544203-data-warehouse-test-engineer](https://www.wearedevelopers.com/jobs/ext/4544203-data-warehouse-test-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Warehouse Test Engineer - **Company:** Yantran Llc - **Location:** Dearborn, MI, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Test Suite, Artificial Intelligence, ARM Architecture, Automation of Tests, BigQuery, Data Warehousing, Error Codes, JSON, Standard Sql, SQL Databases, SQLAlchemy, System Testing, Scripting, Google Cloud, Postman, Sql Optimization, Large Language Models, Pytest, Star Schema, Restful APIs, Looker Analytics, Api Management - **Published:** November 3, 2026 - **Apply:** https://www.thejobnetwork.com/job/b67955b6-3d92-4f79-886d-9e675103a782/data-warehouse-test-engineer ## About the Role Test Engineering: 5+ years designing and executing functional, regression, integration, and negative test suites. Experience with AI/ML system testing or conversational AI testing strongly preferred. API Testing: REST API testing using tools such as Postman, pytest, or equivalent. Experience validating JSON schemas, HTTP error codes, and streaming responses (SSE). SQL / BigQuery: Advanced SQL authoring in BigQuery Standard SQL; window functions, CTEs, date arithmetic, SAFE functions, STRUCT/ARRAY handling. Must be able to independently write complex validation queries against a multi-table star schema. Defect Documentation: Ability to write precise, reproducible defect reports that include expected SQL, actual SQL, expected result set, and actual result set. Bank Domain Knowledge: Understanding of retail/commercial bank operations: deposits, accounts, transactions, AML, KYC, fraud, compliance. Ability to interpret bank KPIs and business rules without extensive hand-holding. Critical Thinking Business Analysis: Ability to read a business question, understand the intended meaning, independently determine the correct SQL answer, and validate whether an AI system answered correctly, not just syntactically but semantically. Preferred Skills: Experience testing LLM-based or NL-to-SQL systems (Cortex, Looker, ThoughtSpot, or similar) Familiarity with GCP services: BigQuery, Cloud Run, Firestore, Dataplex, IAP Python scripting for test automation (pytest, SQLAlchemy, google-cloud-bigquery SDK) SCD2 / data warehousing concepts (bitemporal tables, slowly changing dimensions) Regulatory knowledge: GLBA, FCRA, BSA/AML, Client 239, SOX data quality Experience with data quality testing and data reconciliation Knowledge Graph or ontology concepts Automotive finance domain knowledge