Sr. Distinguished, Data Engineer - Enterprise Data Storage and Consumption Platforms Data Engineer - Remote-eligible

Capital One Capital One · Banking · Richmond, VA

This role is for a Sr. Distinguished Data Engineer focused on enterprise data storage and consumption platforms, specifically maturing platform scalability, operational excellence, performance, and resiliency. It requires deep expertise in AWS, Lakehouse architecture, Snowflake, Databricks, and BI tools. The role involves building awareness, driving adoption of modern technologies, improving system reliability, and leading technical strategy.

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. Identify, benchmark and contribute towards opportunities to improve system availability, security, reliability, cost optimization and performance
  3. 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
  4. Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
  5. Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization

Skills

Required

  • Bachelor's Degree
  • 7 years of experience in software engineering or data engineering
  • 5 years of people management experience
  • 3 years of experience with Big Data and data streaming
  • 3 years of experience with cloud-based data platforms (Amazon Web Services, Microsoft Azure, Google Cloud Platform)
  • 9 years of experience in data engineering writing production quality code with a focus on distributed systems

Nice to have

  • Masters' Degree
  • 10+ years of experience in data engineering
  • 3+ years of experience implementing big data frameworks and processing solutions
  • 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
  • 5+ years of experience with Agile engineering practices
  • 8+ years in-depth experience with the Hadoop stack (MapReduce, Pig, Hive, Hbase)
  • 8+ years experience with NoSQL implementation (Mongo, Cassandra)
  • 8+ years experience developing Java based software solutions
  • 8+ years experience in at least one scripting language
  • 8+ years experience developing software solutions to solve complex business problems
  • 8+ years experience with Relational Database Systems and SQL
  • 8+ years experience designing, developing, and implementing ETL
  • 8+ years experience with UNIX/Linux including basic commands and shell scripting
  • 8+ years of experience providing technical leadership
  • 8+ years of experience leading the full life-cycle of IT development and platform support

What the JD emphasized

  • production quality code
  • distributed systems
  • data engineering
  • data modeling
  • ETL