Data Warehouse Test Engineer
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AI Summary
The Data Warehouse Test Engineer will design and execute complex functional, regression, and integration test suites for AI/ML and data systems. They are responsible for validating AI-generated SQL queries against multi-table star schemas and documenting precise defect reports.
Job Title: Data Warehouse Test Engineer
Location: Dearborn, MI (Remote)
Location: Dearborn, MI (Remote)
Required Skills:
· 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 / Big Query: Advanced SQL authoring in Big Query 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 handholding.
· 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, BCBS 239, SOX data quality
· Experience with data quality testing and data reconciliation
· Knowledge Graph or ontology concepts
Automotive finance domain knowledge
This is a remote position.
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