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Petal // credit card
Engineering, Full Time    New York City    Posted: Thursday, October 01, 2020
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The Petal mission

At Petal, we're using fresh thinking & cutting-edge technology to make credit honest, simple & accessible. We use machine learning to analyze more data in our credit decisions, which means more people qualify, even if they've never had credit before. And we use behavioral science & smart, intuitive design to offer a simple, customer-centric product that's engineered to achieve better financial outcomes -- with straightforward terms & no fees whatsoever. The result is an exciting new approach to credit that has the potential to radically expand credit access & improve the lives of millions of consumers, shaking up a trillion dollar industry in the process.

To do this, we're bringing together exceptional talent from across disciplines & industries to shape the future of financial services & improve the lives of our customers in a meaningful way.

At Petal, we're looking for people with kindness, positivity, & integrity. You're encouraged to apply even if your experience doesn't precisely match the job description. Your skills & potential will stand out-and set you apart-especially if your career has taken some extraordinary twists & turns. At Petal, we welcome diverse perspectives from people who think rigorously & aren't afraid to challenge assumptions.

The Engineering Manager, Data role

We're looking for a leader on our Data Engineering team to work closely with Product Managers, Analysts, Data Scientists & Software Engineers to support new product roadmaps & our existing operations by building the data architecture that informs & drives insights for Petal. Ideally, you have a deep understanding of data engineering best practices & you're excited about organizing complex data sets & making them useful across the organization. As an Engineering Manager you'll manage project goals, contribute to product strategy & help develop your team. As the technical leader of a growing team, you'll also be responsible for the technology choices, data architecture, & scalability of our data infrastructure.
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