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Block
Bay Area, CA, United States of America
Source: Block careers · View original posting
From Block's posting. “We” and “our” refer to the employer.
It all started with an idea at Block in 2013. Initially built to take the pain out of peer-to-peer payments, Cash App has gone from a simple product with a single purpose to a dynamic ecosystem, developing unique financial products, including Afterpay/Clearpay, to provide a better way to send, spend, invest, borrow and save to our 50+ million monthly active customers. We want to redefine the world’s relationship with money to make it more relatable, instantly available, and universally accessible.
Today, Cash App has thousands of employees working globally across office and remote locations, with a culture geared toward innovation, collaboration and impact. We’ve been a distributed team since day one, and many of our roles can be done remotely from the countries where Cash App operates. No matter the location, we tailor our experience to ensure our employees are creative, productive, and happy.
As a Data Engineer, you will handle everything from data architecture and modeling to data pipeline tooling and dashboarding. You will enable a range of other engineering and business teams to make impactful business decisions by laying the foundation of our large and unique datasets that span across multiple products. This role will support the product data engineering team.
The Product Data Engineering Team at Block builds and maintains the curated data foundation that powers all of Block's product lines — Cash App, Square, Afterpay, and Tidal. We transform raw event streams, transactional systems, and operational data into governed, tested, and reliable analytical assets across domains including banking, lending, commerce, investing, checkout, and AI assistants.
We partner with Product, Engineering, Data Science, Machine Learning, and Applied AI teams to deliver the metrics, experimentation frameworks, and ML-ready datasets that enable Block's products to grow, improve, and serve customers at scale.
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