Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
New York, NYMcLean, VAChicago, IL
Salary
$179,400–$204,700 / yr
Employment
Full-time
Posted
6 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k
This role $192k
$141k most similar roles pay here $234k

This role pays more than 51% of similar roles. Most pay $149,800–$211,200 — the shaded band above. At the midpoint, this role pays about $192k versus about $180k 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 1743 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 947 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Data Engineer Manager

Data Engineer 4 (Manager, IC) joins a collaborative team to design, develop, and support technical solutions within an Agile environment. The role involves building robust cloud-first data solutions, designing scalable pipelines, and implementing data security standards like encryption and fine-grained access control. You will architect common engineering patterns to ensure code quality while mentoring others in the data community. Key responsibilities include collaborating with product managers and software engineers to deliver high-performing systems for financial empowerment. The required technical stack includes Python, Spark, SQL, and Scala, alongside experience with distributed microservices, lakehouse architecture, and full-stack systems. You will work with open-source relational and NoSQL databases, as well as cloud platforms like Databricks and Snowflake. This role addresses the challenge of managing large volumes of data while ensuring operational efficiency and reliability across complex data platforms.

What you'll do

  • Design, develop, test, and support full-stack technical solutions using Python, Spark, and cloud platforms like Databricks or Snowflake.
  • Architect and enforce common data engineering design patterns to ensure code quality and reusability across pipelines.
  • Build scalable, resilient, and operationally efficient data pipelines to handle increasing volumes of business data.
  • Implement data security standards including encryption and fine-grained access control to ensure regulatory compliance.
  • Influence a team of developers and scientists by providing expertise in machine learning and lakehouse architecture.
  • Communicate complex technical concepts and data outcomes clearly to both internal and external stakeholders.
  • Develop robust cloud-first data solutions that provide high-quality experiences for customers.

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 solutions (preferred).
  • 2+ years of experience in Agile environments, user-centric products, and data observability or orchestration tools (preferred).

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