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On this team, you will be responsible for building and hosting ML models. You will collaborate with a team of data scientists to build data pipelines for training ML models, host the models in cloud infrastructure and score the models using distributed processing frameworks such as Spark. Working on automation of existing processes using AWS provided services such as Lambda, Step functions, EMR, and CICD pipelines. As well as a lot of SQL queries to retrieve and store data in the Snowflake warehouse.
What You’ll Do:
Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, 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
Utilize programming languages like Python, SQL and Scala and Open Source RDBMS, Container Orchestration services including Docker and Kubernetes, and a variety of AWS tools and services
Basic Qualifications:
Bachelor’s Degree
At least 3 years of professional software engineering experience (Internship experience does not apply)
Preferred Qualifications:
5+ years of experience in at least one of the following: Python, SQL, Snowflake
1+ years of experience with AWS, GCP, Azure, or another cloud service
1+ years of experience in open source distributed processing of big data workloads (PySpark framework)
2+ years of experience in Agile practices
. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
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