Senior Data Engineer (IC) — AI-Driven Risk Tech

Capital One; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking a Data Engineer 4 (Manager IC) in its Risk Tech group in New York, NY. You will design, build, and operate cloud-first data solutions, collaborating with data scientists, analysts, and engineers to enable ML-driven risk management and proactive issue detection.

The role emphasizes scale, security, and governance across data platforms, with leadership responsibilities and the opportunity to shape enterprise data engineering practices.

Qualifications

• Bachelor’s or higher in CS or related quantitative field.
• At least 4 years of application development experience.
• At least 2 years of distributed data experience.
• At least 2 years of SQL experience.
• At least 2 years of experience in one programming language (Python, Java, or Scala).
• At least 2 years of data pipeline design and development experience.
• At least 1 year of data modeling and end-to-end data solutions using relational and non-relational DBs.

Responsibilities

• Collaborate with Agile teams to design, develop, test, and support data solutions.
• Influence teams with ML, microservices, lakehouse architecture, and full-stack systems.
• Utilize Python, Spark, and cloud data warehousing platforms like Databricks and Snowflake.
• Mentor data community members and stay current with data trends and technologies.
• Design and deliver cloud-first data solutions for scalable, secure data experiences.

Skills

Python

SQL

Java/Scala

Data modeling

Team collaboration

Education

Bachelor’s Degree in Computer Science or related quantitative field

Tools

EMR

Spark

Databricks

Airflow

Snowflake

Redshift

Job description

Capital One is seeking a Data Engineer 4 (Manager IC) in its Risk Tech group in New York, NY. You will design, build, and operate cloud-first data solutions, collaborating with data scientists, analysts, and engineers to enable ML-driven risk management and proactive issue detection.

The role emphasizes scale, security, and governance across data platforms, with leadership responsibilities and the opportunity to shape enterprise data engineering practices.