Distinguished Data Engineer - Machine Learning
1750 Tysons (12023), United States of America, McLean, Virginia Distinguished Data Engineer - Machine Learning At Capital One, we believe in the values of excellence and doing the right thing. We are a technology-oriented company delivering financial products to market through modern technology and constant innovation at a massive scale. Distinguished Engineers are Deep technical experts, senior-level individual contributors and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices Visionaries, helping solve Capital One s toughest technology challenges, to deliver on business needs that directly impact the lives of millions of our customers and associates Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Supporters, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities Those who gain the trust and confidence of those around them, from hands on engineers to executives Whether a member of our engineering or architecture teams, Distinguished Engineers are individual contributors expected to solve problems in a fast-paced, collaborative, and iterative delivery environment. In order to meet these demands, candidates should be influential engineering leaders with deep technology expertise, and a collaborative style that brings others into the decision-making process. They will significantly impact the Tech agenda within their organization and devise clear roadmaps to deliver next generation technology solutions across organizational boundaries. The Distinguished Engineer will be a hands-on (see: codes) individual contributor that will be part of the leadership team supporting our Marketing, Decision and Enablement, and Decisioning/Machine Learning Platform team within the Retail and Direct Technology organization (supports Capital One Bank). They will be responsible for tackling our hardest problems, establishing patterns, collaborating across teams and lines of business, and bringing SME-level knowledge around Data Engineering and Machine Learning Engineering domains. It is critically important to be able to tackle problems specifically (hands to keyboard) and influence (through engineering engagement) to scale our practice. Responsibilities: Design and develop cutting-edge solutions, using existing and emerging technology platforms specific to Data Engineering and Machine Learning Engineering (feature calculation, streaming and batch, machine learning lifecycle and platforms) Build real-time and batch machine learning solutions at scale Partner closely with Data Scientist to operational, scale, and contribute to model development lifecycle Leverage sound judgment and problem solving to tackle some of Capital One s most critical problems and connect the dots to broader implications of the work (as both an individual contributor and influencer) Build awareness, increase knowledge and drive adoption of modern technologies and architecture patterns, sharing customer and engineering benefits to gain buy-in (working closely with leaders, other SMEs, and engineers) Strike the right balance between lending expertise and providing an inclusive environment where others ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team (balance being a great coach and listener) Promote a culture of engineering excellence and being well-managed, using opportunities to reuse and innersource solutions where possible (always consider resiliency and impact; major focus on customer experience) Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an integrated manner Design, architect, and help implement a solution to meet our software version management challenges Design, architect, and help implement a system of record to monitor our usage of open source software Design, architect, and help implement a recommendation engine to help Capital One engineering teams comply with open source software version policies and procedures Facilitate the integration of these solutions into the overall Capital One SDLC processes Basic Qualifications: Bachelor s Degree At least 8 years of data engineering experience At least 5 years of experience coding in Java, Scala, or Python At least 3 years of experience working with Machine Learning At least 3 years of experience working with data streaming solutions At least 3 years of experience working with Big Data At least 3 years of experience in Spark, PySpark, or Flink Preferred Qualifications: Masters Degree 10+ years of data engineering experience 8+ years of experience coding in Java, Scala, or Python 5+ years of experience working with Machine Learning 4+ years of experience with AWS Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.