Senior Lead Data Engineer (bank Tech)

Capital One Capital One · Banking · Wilmington, DE +1

Senior Lead Data Engineer role at Capital One within the Bank Tech domain, focusing on building data infrastructure for smart decisions and integrating data and AI capabilities. The role involves designing, developing, and implementing technical solutions, leading developers, and utilizing various data technologies and cloud platforms. The team's focus is on evolving predictive insights and scaling AI-driven decisioning models.

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 Python and Java 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 (AWS, Microsoft Azure, Google Cloud)

Nice to have

  • Python
  • SQL
  • 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 including basic commands and shell scripting
  • Agile engineering practices
  • interactive AI tooling

What the JD emphasized

  • big data technologies
  • cloud computing
  • Distributed data/computing tools
  • real-time data and streaming applications
  • NoSQL implementation
  • data warehousing experience