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Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)

Capital One · Remoto Brasil · Flexible / Remote

Publicada em 29/10/2026

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Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Data Engineers who are passionate about marrying data with emerging technologies. In this role, you'll be at the forefront of driving a major transformation across Capital One.What You'll Do:Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologiesInfluence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systemsUtilize programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and SnowflakeShare your passion for staying on top of trends in data, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the data communityCollaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowermentIndependently design, build and deliver world-class cloud data solutions and applications with little or no support from supervisors or managersArchitect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelinesServe as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alig
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