Senior Quality Engineer, Data Platform

Job description

We are looking for a Senior Quality Engineer to join our Data Platform Quality Engineering team. In this role, you will drive quality across the systems that move, transform, and surface financial data for FloQast's customers — spanning ERP integrations, large-scale data processing, and the accounting workflows that thousands of finance teams depend on every day. You will design and scale automation frameworks that validate data accuracy, pipeline reliability, and system performance, while partnering closely with data engineers, backend developers, and product teams. What You’ll Do: 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. What You'll Bring: 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. Nice to Haves: 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.