Data Engineer Manager

Capital One Financial

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Richmond, VAMcLean, VA
Salary
$197,300–$225,100 / yr
Posted
5 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $176k
This role $211k
$130k most similar roles pay here $235k

This role pays more than 79% of similar roles. Most pay $140,000–$211,200 — the shaded band above. At the midpoint, this role pays about $211k versus about $176k 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 836 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 829 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) 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 within a full-stack environment. The individual will architect data pipelines and platforms focused on scalability, resilience, and operational efficiency while ensuring robust security standards like encryption and access control. Key responsibilities include mentoring others in the data community and communicating complex technical concepts to stakeholders. The role requires proficiency in Python, Spark, SQL, and Scala, alongside experience with distributed microservices, lakehouse architecture, and cloud-based platforms including Databricks and Snowflake. Candidates will work with both relational and NoSQL databases to solve critical business problems involving automated risk detection and the development of high-quality, reusable data products.

What you'll do

  • Design, develop, test, and support technical solutions using full-stack development tools and technologies.
  • Influence a team of developers, data analysts, and data scientists in machine learning and distributed microservices.
  • Build and deploy cloud-first data solutions using Python, Spark, Databricks, and Snowflake.
  • Architect and enforce common data engineering design patterns to ensure code quality and reusability.
  • Design and build scalable, resilient data pipelines and platforms to handle increasing data volumes.
  • Implement data security standards including encryption and fine-grained access control for regulatory compliance.
  • Communicate 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.
  • At least 2 years of experience with SQL.
  • At least 2 years of experience with one programming language (Python, Java, or Scala).
  • At least 2 years of experience in data pipeline design and development.
  • At least 1 year of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems.
  • Experience with cloud platforms, distributed workloads, real-time pipelines, or NoSQL databases (preferred); experience in Agile environments or developing user-centric products (preferred).

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