Senior Lead Data Engineer - Enterprise Risk & ML

Capital One; North Dakota; On-site; USD 209,000 - 262,000; Full time

Job summary

Capital One seeks a Senior Lead Data Engineer for Enterprise Risk Management to drive a major data transformation. You will lead a team across Agile environments, designing and delivering cloud-based data solutions using Java, Scala, Python and modern data warehousing tools.

You will mentor engineers, work with ML and distributed systems, ensure robust quality through reviews and tests, and collaborate with product partners to enable data-driven risk decisions across the enterprise.

Qualifications

• Bachelor's Degree required.
• 6+ years of application development experience.
• 2+ years of big data technologies experience.
• 1+ year cloud computing experience (AWS/Azure/GCP).

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions.
• Lead a team of developers with experience in ML, distributed microservices, and full-stack systems.
• Utilize Java, Scala, Python and SQL/NoSQL databases and cloud data warehousing services (Redshift, Snowflake).
• Mentor engineers, stay current with tech trends, and contribute to community knowledge.
• Deliver cloud-based data solutions that empower users and drive business impact.
• Perform unit tests and code reviews to ensure high-quality, performant code.

Skills

Leadership

Mentoring

Team collaboration

Agile practices

Communication

Education

Bachelor's Degree

Master's Degree

Tools

Java

Scala

Python

Redshift

Snowflake

Hadoop

Spark

Kafka

MongoDB

Cassandra

Unix/Linux shell

AWS

Azure

GCP

Job description

Capital One seeks a Senior Lead Data Engineer for Enterprise Risk Management to drive a major data transformation. You will lead a team across Agile environments, designing and delivering cloud-based data solutions using Java, Scala, Python and modern data warehousing tools.

You will mentor engineers, work with ML and distributed systems, ensure robust quality through reviews and tests, and collaborate with product partners to enable data-driven risk decisions across the enterprise.