Distinguished Data Engineer - Card Data

Capital One Capital One · Banking · San Francisco, CA +4

Distinguished Data Engineer role focused on managing and leveraging large-scale, sensitive data for financial services. The role involves architecting high-availability data solutions, working with cloud technologies (Snowflake, Kafka, AWS), and collaborating with ML Scientists and Product Managers. While the role supports ML models and predictive analytics, its core focus is on data engineering and architecture rather than building AI models directly.

What you'd actually do

  1. Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
  2. 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
  3. Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
  4. Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization
  5. Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner
  6. Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent

Skills

Required

  • Bachelor's Degree
  • 7 years of experience in data engineering
  • 3 years of experience in data architecture
  • 2 years of experience building applications in AWS

Nice to have

  • Masters’ Degree
  • 9+ years of experience in data engineering
  • 3+ years of data modeling experience
  • 2+ years of experience with ontology standards for defining a domain
  • 2+ years of experience using Python, SQL or Scala
  • 1+ year of experience deploying machine learning models
  • 3+ years of experience implementing big data processing solutions on AWS

What the JD emphasized

  • petabytes of sensitive, real-time and batch data
  • fraud detection models
  • personalized reward systems
  • regulatory compliance reporting
  • machine learning
  • predictive analytics
  • AWS