Data Engineer Manager

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Richmond, VA
Salary: $179,400–$204,700 / yr
Employment: Full-time
Posted: 9 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $177k

This role $192k

$134k most similar roles pay here $220k

This role pays more than 57% of similar roles. Most pay $141,950–$211,200 — the shaded band above. At the midpoint, this role pays about $192k 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.

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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 for code quality, and developing scalable pipelines that ensure operational efficiency and security compliance. 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, Java, and Scala, utilizing tools such as Databricks, Snowflake, and various NoSQL databases like Mongo or Cassandra. Your work focuses on solving complex business problems by creating high-performance data platforms and products that manage large volumes of structured and unstructured data to drive meaningful user experiences in the financial sector.

Skills

Python SQL Spark Scala Java Databricks Snowflake AWS Azure NoSQL Redshift Airflow Dagster Splunk Monte Carlo EMR Glue Agile

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.
Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across pipelines.
Build scalable, resilient, and efficient data pipelines to handle increasing volumes of data and business demands.
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 internal and external stakeholders to drive alignment.
Mentor other members of the data community and stay current on emerging trends and technologies.

What we're looking for

Bachelor's Degree in Computer Science or a related 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 databases.
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, data observability/orchestration tools, and developing user-centric reusable data products (preferred).

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