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Software Engineer, Data Privacy Technologies

stripe · N/A

по договорённости

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Software Engineer, Data Privacy Technologies

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe will succeed at our mission of increasing the GDP of the internet only if we prove ourselves worthy of our users’ trust. The Data Privacy Technologies team contributes to this by building systems that allow Stripe to deeply reason about and protect user data, at scale. As an engineering team, we leverage system design and applied AI/ML to innovate in data classification and pseudonymization techniques such as tokenization, redaction, filtering, and masking.

What you’ll do

Responsibilities

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

Preferred qualifications

Показать как в источнике
Software Engineer, Data Privacy Technologies

<h2>Who we are</h2> <h3>About Stripe</h3> <p><span style="font-weight: 400;">Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.</span></p> <h3>About the team</h3> <p>Stripe will succeed at our mission of increasing the GDP of the internet only if we prove ourselves worthy of our users’ trust. The Data Privacy Technologies team contributes to this by building systems that allow Stripe to deeply reason about and protect user data, at scale. As an engineering team, we leverage system design and applied AI/ML to innovate in data classification and pseudonymization techniques such as tokenization, redaction, filtering, and masking.</p> <h2>What you’ll do</h2> <h3>Responsibilities</h3> <ul> <li>Design, build, and operate core infrastructure used by all of Stripe’s engineering teams, for example to automatically annotate and obfuscate sensitive data</li> <li>Make impactful decisions at the intersection of privacy, security and productivity — the edge cases, failure modes and tradeoffs</li> <li>Collaborate closely with legal, product, compliance, operations and other engineering teams to embed best practices for data protection into how products and infrastructure are built</li> <li>Improve engineering standards and processes</li> </ul> <h2><strong>Who you are</strong></h2> <p><span style="font-weight: 400;">We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.</span></p> <h3>Minimum requirements</h3> <ul> <li>2-5 years of software engineering experience&nbsp;</li> <li>Experience building and owning highly available, scalable and performant systems in a high-stakes production environment&nbsp;</li> <li>Empathy, excellent communication skills and a deep respect for the power of collaboration</li> <li>A learning mindset&nbsp;</li> <li>The ability to think creatively and holistically about reducing risk in a complex, fast-changing environment&nbsp;</li> <li>The ability to drive next steps when encountering ambiguous problems without clear ownership</li> </ul> <h3><strong>Preferred qualifications</strong></h3> <ul> <li>Data platform/systems experience</li> <li>Applied AI/ML experience</li> <li>Privacy or security experience</li> </ul>

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