Capital One
Data Engineer 4 (Manager, IC)-Risk Tech
$179K–$225K
McLean, VA +1 · Manager · Full-time · Posted Sep 24, 2026
- Location
- McLean, VA
Richmond, VA - Experience
- At least 4 years in application development, 2 years in distributed data, SQL, a programming language, and data pipeline design and development, and 1 year in data modeling and end-to-end solutions. Preferred experience ranges from 2+ to 7+ years, depending on the area.
- Education
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- Visa sponsorship
- Will not sponsor a new applicant for employment authorization or provide immigration-related support for this position.
About the job
Build and operate scalable cloud data pipelines and platforms for risk-management solutions, including products powered by AI.
What you'll do
- Design, develop, test, implement, and support technical solutions across data platforms and pipelines.
- Architect data engineering patterns and build secure, scalable solutions with attention to resilience and operational efficiency.
- Collaborate with Agile teams and stakeholders, communicate technical outcomes, and mentor data community members.
What they ask for
- Bachelor's Degree or higher in Computer Science or a related quantitative field.
- At least 4 years of application development experience; internships do not apply.
- At least 2 years of experience in distributed data, SQL, one programming language (Python, Java, or Scala), and data pipeline design and development.
- At least 1 year of experience in data modeling and end-to-end data solutions using relational and non-relational database systems.
Nice to have
- Experience with public cloud environments, distributed data or compute workloads, and real-time or streaming pipelines.
- Experience with data observability or orchestration, NoSQL databases, data warehousing, Agile development, or reusable data products.
Pay
$197,300 - $225,100 USD base salary (McLean, VA); $179,400 - $204,700 USD base salary (Richmond, VA)
Tools
Python, Spark, SQL, Java, Scala, Databricks, Snowflake, Airflow
AI focus
Build and deploy proprietary risk-management solutions powered by AI; products also use machine learning to prevent risks and automatically detect issues.
Model-written summary · the original posting is authoritative