Senior Data Engineer — AI & Risk Platform

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Job summary

Capital One seeks a Data Engineer to join Risk Tech in McLean, VA, driving cloud-first data solutions and collaborating with cross-functional teams. You will work across data scientists, engineers, and product managers to deliver robust data platforms.

The position emphasizes Python, Spark, Databricks, and Snowflake, with an focus on scalable pipelines, data security, and governance. Mentorship and ongoing learning are encouraged.

Qualifications

• Bachelor's degree or higher in CS or related quantitative field.
• 4+ years of experience in application development (no internships).
• 2+ years of experience with distributed data.
• 2+ years of experience with SQL.
• 2+ years of experience with one programming language (Python, Java, or Scala).
• 2+ years of experience in data pipeline design and development.
• 1+ year of experience in data modeling and end-to-end data solutions with relational and non-relational databases.

Responsibilities

• Collaborate with Agile teams to design and implement data solutions.
• Influence a team of developers, data analysts and data scientists.
• Use Python, Spark, and cloud data warehouses like Databricks and Snowflake.
• Mentor peers and stay current with data trends and technologies.
• Deliver cloud-first data solutions driving business value and risk insights.
• Design scalable data pipelines and enforce reusable patterns.
• Communicate data outcomes clearly to stakeholders.

Skills

Python

SQL

Scala/Java

Machine learning basics

Education

Bachelor's Degree in CS or related field

Tools

EMR

Spark

Glue

Databricks

Job description

Capital One seeks a Data Engineer to join Risk Tech in McLean, VA, driving cloud-first data solutions and collaborating with cross-functional teams. You will work across data scientists, engineers, and product managers to deliver robust data platforms.

The position emphasizes Python, Spark, Databricks, and Snowflake, with an focus on scalable pipelines, data security, and governance. Mentorship and ongoing learning are encouraged.