Senior Distinguished Data Engineer (remote-eligible)

Capital One Capital One · Banking · McLean, VA +2 · Remote

Senior Distinguished Data Engineer role focused on data strategy, governance, analytics, and AI integration within Capital One's Enterprise Data business unit. The role involves building awareness and adoption of modern technologies, mentoring teams, and leading the creation of next-generation talent. Requires significant experience in data engineering, data architecture, and AWS, with preferred experience in data modeling, ontology standards, Python/SQL/Scala, deploying ML models, and big data processing on AWS.

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
  • 9 years of experience in data engineering
  • 5 years of experience in data architecture
  • 3 years of experience building applications in AWS

Nice to have

  • Masters' Degree
  • 10+ 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

  • 1 year of experience deploying machine learning models