QA Engineer (Python / SDET)

Tritone Analytics is building a forensic royalty auditing platform for the music industry. We ingest messy, real-world financial data from labels, distributors, and publishers—and turn it into clean, structured systems that power analysis and AI workflows.

We’re looking for a junior-to-mid level QA Engineer to own testing across our core data systems.

This is not a traditional QA role. You’ll be working with data pipelines, not just UI flows.

• Own quality across a Python-based royalty data pipeline (CSV/XLSX → normalized data)
• Write and maintain tests across: unit, integration, and E2E (Playwright)
• Data validation (row counts, column mappings, financial logic)
• Expand E2E coverage for our Gradio dashboard (upload → process → export)
• Validate transformations using SQL (DuckDB)
• Improve and maintain CI/CD pipelines (GitHub Actions)
• Identify gaps in test coverage and proactively build solutions

• Validate that 100K+ rows from a label ingestion pipeline are correctly mapped and normalized
• Build tests to ensure financial calculations remain consistent across multiple data sources
• Expand end-to-end coverage so ingestion changes don’t break downstream outputs

• 1–2 years of experience with Python (pytest)
• Comfortable writing SQL queries to validate data
• Strong attention to detail—especially with structured data
• Ability to work independently in a small team

• Experience with Playwright or browser automation (Selenium is fine)
• Exposure to CI/CD tools (GitHub Actions, Jenkins, etc.)
• Interest in data pipelines, ETL, or backend systems

• Python 3.12+, pytest
• DuckDB (data processing)
• Gradio (UI)
• GitHub Actions (CI/CD)
• 3,000+ existing tests across 100+ files

• pandas, DuckDB, or data validation tools (pandera, great_expectations)
• Experience with financial, analytics, or music-related data
• Performance testing or parallelization (pytest-xdist)

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