Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Richmond, VAMcLean, VACambridge, MA
Salary: $197,300–$225,100 / 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 $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 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

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As a Data Engineer 4 (Manager, IC), you will join a collaborative team to design, develop, test, and support technical solutions within a full-stack development environment. You will be responsible for building robust cloud-first data solutions, architecting common engineering design patterns to ensure code quality, and developing scalable data pipelines that prioritize resilience and operational efficiency. The role involves influencing teams of developers and data scientists while mentoring others in the data community. You will work with technologies including Python, Spark, SQL, and Scala, utilizing open-source relational and NoSQL databases alongside cloud platforms like Databricks and Snowflake. Your work focuses on solving complex business problems by delivering high-quality data products and infrastructure that manage large volumes of information while maintaining strict security standards and ensuring compliance with data privacy regulations.

Skills

Python Spark SQL Scala Java Databricks Snowflake AWS Azure NoSQL MongoDB Cassandra DynamoDB Redshift Airflow Dagster Splunk Agile

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 lakehouse architecture.
Build and deliver 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 that perform under high volume and demand.
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, streaming pipelines, NoSQL databases, or data observability tools (preferred).

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