Senior Quality Engineer, Data Platform
Summary
Senior Quality Engineer on FloQast's Data Platform QE team, designing and scaling automated test frameworks for data pipelines, ETL/ELT workflows, REST APIs, and backend services that process financial data, using JavaScript/TypeScript, Python, SQL, and cloud data warehouses like Snowflake.
What You’ll Do:
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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.
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Validate data integrity, schema correctness, and transformation accuracy across ERP-to-FloQast ingestion flows (NetSuite, Sage Intacct, SAP, and others).
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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.
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Build and maintain data quality validation test suites — including row-count checks, referential integrity, financial aggregation accuracy, and cross-system reconciliation.
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Integrate automated tests into CI/CD pipelines with clear test reporting and alerting.
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Contribute to test data management strategies, including synthetic financial data generation and environment seeding for data platform services.
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Collaborate with release teams on release validation, triage defects, and drive root cause analysis on data discrepancies.
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Mentor junior QE engineers and champion a data-quality-first testing culture across the team.
What You'll Bring:
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Bachelor’s or Master’s degree in Computer Science or a related field.
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5+ years of QA automation experience, with at least 2+ years testing data pipelines, data warehouses, or data-intensive backend services.
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Strong proficiency in JavaScript/TypeScript and Python, and test frameworks (Jest, Mocha, Playwright, Cypress).
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Hands-on experience with SQL and data validation — writing complex queries to verify transformation logic, aggregations, and financial data accuracy.
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Experience testing against Snowflake, Redshift, or similar cloud data warehouses.
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Solid understanding of ETL/ELT concepts — data ingestion, transformation, schema evolution, and lineage.
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Experience with REST API testing and backend service validation.
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Proficiency with GitHub Actions and version control (Git).
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Strong debugging skills for data discrepancies — able to trace an issue from UI through API to pipeline and raw data store.
Nice to Haves:
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Prior exposure to ERP systems (NetSuite, Sage Intacct, SAP, or similar) and how data flows between source systems and a downstream platform.
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Familiarity with financial domain concepts — general ledger, month-end close, or multi-entity accounting.
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Some experience with observability or data monitoring tools.
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Background in SaaS or cloud-native architectures.
Here’s Why You Should Apply
- What is engineering working on? Our FQ Engineering Blog showcases a number of our recent efforts straight from the engineers working on them. Check it out!Skills
As published by lever · 4 questions
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