Sr. Lead Data Engineer

Capital One Capital One · Banking · McLean, VA +1

This role is for a Sr. Lead Data Engineer at Capital One, focusing on designing, developing, and implementing technical solutions. The role involves leading a team of developers with experience in machine learning, distributed microservices, and full-stack systems, utilizing various programming languages and cloud-based data warehousing services. The primary focus is on data engineering and supporting ML initiatives, rather than direct AI/ML model development.

What you'd actually do

  1. Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
  2. Lead a team of developers with deep experience in machine learning, distributed microservices, and full stack systems
  3. Utilize programming languages like Java, Scala, Python and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake
  4. Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
  5. Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment

Skills

Required

  • Application development
  • Big data technologies
  • Cloud computing (AWS, Microsoft Azure, Google Cloud)

Nice to have

  • Python
  • SQL
  • Scala
  • Java
  • Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
  • Real-time data and streaming applications
  • NoSQL implementation (Mongo, Cassandra)
  • Data warehousing experience (Redshift or Snowflake)
  • UNIX/Linux
  • Agile engineering practices
  • Interactive AI tooling

What the JD emphasized

  • machine learning
  • full stack systems
  • big data technologies
  • cloud computing
  • real-time data and streaming applications
  • NoSQL implementation
  • data warehousing experience
  • Agile engineering practices