Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VA
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 $177k

This role $211k

$132k most similar roles pay here $235k

This role pays more than 80% of similar roles. Most pay $141,950–$211,200 — the shaded band above. At the midpoint, this role pays about $211k 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 1554 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 796 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 an Agile 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 and platforms. The role involves influencing a team of developers and data scientists while mentoring others in the data community. You will work with technologies including Python, Spark, SQL, Scala, and Java, utilizing tools such as Databricks, Snowflake, and various NoSQL databases like MongoDB or Cassandra. Your work focuses on solving complex business problems by implementing distributed microservices, lakehouse architecture, and real-time streaming pipelines to ensure data security and performance across large-scale platforms while managing high volumes of structured and unstructured data.

Skills

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

What you'll do

Design, develop, test, and implement 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, maintainability, 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 compliance with privacy regulations.
Influence a team of developers, analysts, 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.
Deliver robust cloud-first data solutions that provide high-quality experiences for end users.

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 2 years of experience with one programming language such as Python, Java, or Scala.
At least 1 year of experience in data modeling and designing end-to-end solutions using relational and non-relational systems.
7+ years of experience in application development with proficiency in Python, SQL, Scala, or Java (preferred).
4+ years of experience in cloud environments, distributed workloads, real-time pipelines, NoSQL databases, or data warehousing (preferred).
2+ years of experience in Agile environments, user-centric products, and data observability or orchestration tools (preferred).

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