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Senior Quality Engineer, Data Platform

FloQast
San Jose, USA
Full-time
Senior · 5+ years experience
Hybrid
USD 144000-213000 yearly / year
Discovered 1 weeks ago
JavaScriptTypeScriptPythonJestMochaPlaywright
Free

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  • Design, build, and maintain automated test frameworks across the full data stack — covering data pipelines, ETL/ELT workflows, REST APIs, and backend services that power large-scale financial data processing.
  • Validate data integrity, schema correctness, and transformation accuracy across ERP-to-FloQast ingestion flows (NetSuite, Sage Intacct, SAP, and others).
  • Identify performance bottlenecks and reliability gaps in data-heavy workflows — whether that’s slow ingestion on large customer datasets, pipelines that produce inconsistent results under load, or sync jobs that behave differently across customer environments.
  • Build and maintain data quality validation test suites — including row-count checks, referential integrity, financial aggregation accuracy, and cross-system reconciliation.
  • Integrate automated tests into CI/CD pipelines with clear test reporting and alerting.
  • Contribute to test data management strategies, including synthetic financial data generation and environment seeding for data platform services.
  • Collaborate with release teams on release validation, triage defects, and drive root cause analysis on data discrepancies.
  • Mentor junior QE engineers and champion a data-quality-first testing culture across the team.
  • Bachelor’s or Master’s degree in Computer Science or a related field.
  • 5+ years of QA automation experience, with at least 2+ years testing data pipelines, data warehouses, or data-intensive backend services.
  • Strong proficiency in JavaScript/TypeScript and Python, and test frameworks (Jest, Mocha, Playwright, Cypress).
  • Hands-on experience with SQL and data validation — writing complex queries to verify transformation logic, aggregations, and financial data accuracy.
  • Experience testing against Snowflake, Redshift, or similar cloud data warehouses.
  • Solid understanding of ETL/ELT concepts — data ingestion, transformation, schema evolution, and lineage.
  • Experience with REST API testing and backend service validation.
  • Proficiency with GitHub Actions and version control (Git).
  • Strong debugging skills for data discrepancies — able to trace an issue from UI through API to pipeline and raw data store.
  • Prior exposure to ERP systems (NetSuite, Sage Intacct, SAP, or similar) and how data flows between source systems and a downstream platform.
  • Familiarity with financial domain concepts — general ledger, month-end close, or multi-entity accounting.
  • Some experience with observability or data monitoring tools.
  • Background in SaaS or cloud-native architectures.

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