Data Engineer V Senior Manager Risk Tech

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VARichmond, VA
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $177k

This role $246k

$122k most similar roles pay here $277k

This role pays more than 92% of similar roles. Most pay $137,000–$216,968 — the shaded band above. At the midpoint, this role pays about $246k versus about $177k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 936 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 933 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer V Senior Manager Risk Tech

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Data Engineer 5 (Senior Manager, IC)-Risk Tech joins the Risk Tech team to build and deploy proprietary risk management solutions powered by state-of-the-art AI technology. This role involves collaborating with Agile teams to design, develop, test, and support technical solutions in a full-stack environment. The individual will architect data pipelines and platforms focused on scalability and resilience while mentoring other members of the data community. Key responsibilities include managing large-scale initiatives, making architectural decisions regarding platform choices like Snowflake or Databricks, and ensuring code quality through established design patterns. The role requires proficiency in Python, Spark, SQL, Java, or Scala, along with experience in distributed microservices, lakehouse architecture, and cloud-based data warehousing. The work focuses on creating machine learning tools to detect issues and prevent risks within the risk management domain.

Skills

Python SQL Spark Scala Java Databricks Snowflake AWS Azure NoSQL relational database s Airflow Dagster Redshift EMR Glue Monte Carlo Splunk Agile

What you'll do

Design, develop, and support full-stack technical solutions using Python, Spark, and cloud-based data platforms like Databricks or Snowflake.
Architect and enforce common data engineering design patterns to ensure code quality and reusability across pipelines.
Build scalable, resilient data pipelines and platforms to handle increasing volumes of data and business demands.
Lead large-scale data initiatives by making critical architectural decisions and evaluating platform technologies based on requirements.
Mentor junior engineers and provide technical leadership to a team of developers, analysts, and scientists.
Communicate complex technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment.
Develop robust cloud-first data solutions that integrate machine learning to detect risks and automate issues.

What we're looking for

Bachelor's Degree or higher in Computer Science or a related quantitative field.
At least 6 years of experience in application development.
At least 4 years of experience in distributed data.
At least 4 years of experience with SQL.
At least 4 years of experience programming with Python, Java, or Scala.
At least 4 years of experience designing and developing data pipelines.
At least 2 years of experience in data modeling and designing end-to-end solutions using relational and non-relational systems.
Master's Degree in Computer Science or a related field (preferred); 8+ years of experience in data engineering (preferred).

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