Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
McLean, VARichmond, VA
Salary
$197,300–$225,100 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $174k
This role $211k
$125k most similar roles pay here $236k

This role pays more than 80% of similar roles. Most pay $135,975–$211,200 — the shaded band above. At the midpoint, this role pays about $211k versus about $174k 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 Manager

Data Engineer 4 (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 full-stack technical solutions while influencing a team of developers, data scientists, and analysts. The position focuses on building scalable, resilient data pipelines and cloud-first platforms that utilize machine learning to detect issues and prevent risks. Key responsibilities include architecting common engineering patterns for code quality and implementing security standards like encryption and access control. Candidates will work with Python, Spark, SQL, and Scala while utilizing tools such as Databricks, Snowflake, and NoSQL databases. The role addresses the critical business problem of transforming risk management through automated detection and advanced data-driven tools in a complex environment.

What you'll do

  • Design, develop, test, and support full-stack technical solutions using Python, Spark, and cloud-based data platforms like Databricks or Snowflake.
  • Build and deploy proprietary risk management solutions powered by state-of-the-art AI technology.
  • Architect and enforce common data engineering design patterns to ensure code quality and reusability across pipelines.
  • Design and build scalable, resilient data pipelines that handle high volumes of information efficiently.
  • Implement data security standards including encryption and fine-grained access control to ensure regulatory compliance.
  • Mentor other members of the data community and share expertise on emerging technology trends.
  • Communicate complex technical concepts and data outcomes clearly to internal and external stakeholders.

What we're looking for

  • Bachelor's Degree or higher in Computer Science or a related quantitative field.
  • At least 4 years of experience in application development.
  • At least 2 years of experience in distributed data, SQL, and data pipeline design and development.
  • At least 1 year of experience in data modeling and designing end-to-end solutions using relational and non-relational systems.
  • At least 2 years of experience with one programming language such as Python, Java, or Scala.
  • 7+ years of experience in application development with proficiency in Python, SQL, Scala, or Java (preferred).
  • 4+ years of experience in cloud environments, distributed data workloads, real-time pipelines, and data warehousing (preferred).
  • 2+ years of experience in Agile environments, user-centric products, and data observability or orchestration tools (preferred).

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