Lead Data Engineer (intelligent Foundations and Experiences)

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

Lead Data Engineer role focused on building and pioneering in the technology space, collaborating with Agile teams to design, develop, test, implement, and support technical solutions. The role involves working with machine learning, distributed microservices, and full stack systems, utilizing languages like Java, Scala, and Python, and cloud-based data warehousing services. It also includes mentoring and collaborating with product managers to deliver cloud-based solutions.

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. Work with 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
  6. Perform unit tests and conduct reviews with other team members to make sure your code is rigorously designed, elegantly coded, and effectively tuned for performance

Skills

Required

  • Application development
  • Big data technologies
  • Cloud computing

Nice to have

  • Python
  • SQL
  • Scala
  • Java
  • Public cloud (AWS, Microsoft Azure, Google Cloud)
  • 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
  • Shell scripting
  • Agile engineering practices