Capital One-posted 7 days ago
Full-time • Mid Level
McLean, VA
5,001-10,000 employees

Senior Distinguished Data Engineer Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions. About the Team: You will join the Data Pipelines team within Enterprise Data, serving as a Senior Director-level Individual Contributor (IC). This role demands a visionary and hands-on leader to drive the technical strategy for data pipelines leveraged by all lines of business inclusive of both internal and external data availability. Your focus is on driving innovation, best practices, engineering / delivery acceleration, platform scalability, Operational Excellence, Performance, Resiliency, and being a beacon for other ICs. We require deep expertise in AWS infrastructure, Lakehouse architecture, Kafka, Flink, Spark, Snowflake, and Databricks mature these enterprise-scale systems and execute technical strategy. You will be both visionary, influential, and hands-on writing Python, SQL, Java, and/or Scala code. Our Sr. Distinguished Engineers Are: Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices Visionaries, collaborating on Capital One’s toughest issues, to deliver on business needs that directly impact the lives 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 Evangelists, 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

  • Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
  • 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
  • Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
  • 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 unified manner
  • 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
  • Bachelor’s Degree
  • At least 9 years of experience in data engineering
  • At least 5 years of experience in data architecture
  • At least 3 years of experience in building applications in AWS
  • At least 3 years of experience with Python, Scala, Java, or SQL
  • At least 3 years of experience with Flink or Spark
  • At least 3 years of experience with Kafka
  • At least 3 years of experience with Delta Lake or Iceberg
  • At least 3 years of experience building performant, resilient Big Data solutions
  • 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
  • 3+ years of experience deploying machine learning models
  • 1+ year of experience deploying Agentic AI solutions
  • 3+ years of experience implementing big data processing solutions on AWS or other cloud providers
  • 3+ years of experience with Snowflake or Databricks
  • 3+ years of experience with Data Observability tooling (lineage, data quality, monitoring or alerting)
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