Senior Lead Data Engineer

Capital One Capital One · Banking · McLean, VA +3

Senior Lead Data Engineer at Capital One, focusing on designing, developing, and implementing technical solutions with a team of developers experienced in machine learning and full-stack systems. The role involves utilizing various programming languages and cloud-based data warehousing services, and collaborating with product managers to deliver cloud-based solutions. While the role mentions leading a team with ML experience and leveraging AI tooling, the core responsibilities are centered around data engineering and application development, not directly shipping AI models or agents.

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)
  • Java
  • Scala
  • Python
  • RDBMS
  • NoSQL databases
  • Redshift
  • Snowflake
  • UNIX/Linux
  • shell scripting
  • Agile engineering practices

Nice to have

  • Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
  • real-time data and streaming applications
  • NoSQL implementation (Mongo, Cassandra)
  • interactive AI tooling

What the JD emphasized

  • At least 6 years of experience in application development
  • At least 2 years of experience in big data technologies
  • At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud)
  • 4+ years of experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
  • 4+ years of data warehousing experience (Redshift or Snowflake)