QA Engineer

The financial industry is growing at a record pace, but our data providers are still stuck in the past — with cumbersome onboarding processes, complicated APIs, slow infrastructure, and expensive licensing costs.

Databento is the next-generation market data provider — with the radical idea that you should only pay for the data that you use. We power the world's largest finance and fintech institutions and lower the barrier of entry for small startups.

Since starting in 2019, we've raised over $27.8M in funding and have over 2,000 companies signed up pre-launch. Our team consists of former data users from firms like Two Sigma, Belvedere, Pico, Bloomberg, Pinterest, and Google.

We offer health, dental, disability, and life insurance benefits, as well as 401(k) matching and visa sponsorships. We accommodate 100% remote work, with teammates living around the globe and paid in their local currency.

• Participate in all aspects of testing, including regression, integration, acceptance, performance, and usability testing for frontend and backend application layers.
• Work across teams to understand business goals and technical requirements.
• Develop, implement, and maintain automated test suites and frameworks.
• Organize and document detailed test results. 

• 2+ years as a QA or Test Engineer in at least one of the following domains: electronic trading, information retrieval, data storage, database design, machine learning, distributed computing, security, natural language processing, enterprise SaaS.
• Experience developing in at least two of the following languages: C++, Python, Javascript, and Typescript.
• Experience covering both backend and frontend teams.
• Degree in computer science, applied mathematics, or a related field.

• Experience working in a financial institution, financial data vendor, or any significant provider or consumer of data analytics.
• Experience with financial data (multicast feeds, time series, security references, machine-readable news) or analytics.
• Jenkins, TeamCity, GitLab CI, Docker, Kubernetes, or similar CI/CD tools. 
• Cypress, Jest, Postman, Selenium, or similar test automation tools.
• Broad knowledge of performance optimizations (memory hierarchy and I/O bounds, CPU architecture, kernel bypass networking, lock-free algorithms, compiler behavior, zero copy, instruction pipelining and prefetching).
• Vitess, ClickHouse, kdb, Vertica, Pulsar, or similar clustered databases and messaging platforms. 
• Experience working within a Linux environment.