Senior Data Engineer Role Overview
We are seeking experienced data engineers who are passionate about marrying data with emerging technologies. As a Capital One Data Engineer, you'll have the opportunity to be on the forefront of driving a major transformation within our company.
Key Responsibilities
- Collaborate with Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies.
- Work with a team of developers with deep experience in machine learning, distributed microservices, and full stack systems.
- Utilize programming languages like Python, Java, Scala, and Open Source RDBMS and NoSQL databases and Cloud based data warehousing services such as Redshift and Snowflake.
- 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.
- Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment.
Requirements
- Bachelor's Degree
- At least 3 years of experience in application development (Internship experience does not apply)
- At least 1 year of experience in big data technologies
Preferred Qualifications
- 5+ years of experience in application development including Python, SQL, Scala, or Java
- 2+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
- 3+ years experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
- 2+ year experience working on real-time data and streaming applications
- 2+ year experience working with testing frameworks (Pytest, Behave)
- 2+ years of experience with NoSQL implementation (Mongo, Cassandra)
- 2+ years of data warehousing experience (Redshift or Snowflake)
- 3+ years of experience with UNIX/Linux including basic commands and shell scripting
- 2+ years of experience with Agile engineering practices