Data Engineer 4 (Manager, IC)

Information Technology Senior Management Forum; Richmond (VA); On-site; USD 179,000 - 205,000; Full time

Job summary

Information Technology Senior Management Forum in Richmond, VA, is seeking a Data Engineer 4 (Manager, IC) to design, build, and deploy cloud-first, AI-powered risk solutions for Capital One Risk Tech. The role focuses on scalable data pipelines and strong data security practices, with onsite work in Richmond.

The candidate will partner across GRC and company teams, mentor data professionals, and design robust data platforms to serve millions of Americans.

Qualifications

• 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 databases.

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies.
• Influence developers, data analysts, and data scientists with expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Build using Python and Spark, leveraging open-source relational and NoSQL databases and cloud data warehousing platforms including Databricks and Snowflake.
• Stay current on data trends by experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring members of the data community.
• Partner with product managers and software engineers to deliver robust cloud-first data solutions that support experiences for millions of Americans.
• Independently design, build, and deliver cloud data solutions and applications with little or no support from supervisors or managers.
• Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability across platforms and pipelines.
• Design and build data pipelines and platforms focused on scalability, resilience, and operational efficiency to maintain performance as data and demands grow.
• Implement data security standards, including encryption at rest/transit and fine-grained access control, to support compliance with data privacy regulations.
• Serve as a data engineering ambassador by communicating technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment.

Skills

Distributed data

SQL

Data modeling

Data pipelines design

Education

Bachelor's degree in Computer Science or related quantitative field

Tools

Python

Spark

Databricks

Snowflake

SQL

NoSQL

MongoDB

Cassandra

DynamoDB

EMR

Glue

Airflow

Dagster

Monte Carlo

Splunk

Redshift

AWS

Microsoft Azure

Google Cloud

Scala

Java

Job description

This role supports Capital One Risk Tech by designing, building, and deploying cloud-first, AI-powered risk management solutions. The Data Engineer 4 (Manager, IC) will help partner across GRC and company teams, with a focus on scalable data pipelines and strong data security practices.

Location

Richmond, VA (onsite)

Compensation

Salary Range: USD 179,400 - 204,700 per yearly (Richmond, VA).

Performance based incentive compensation may include cash bonus(es) and/or long term incentives (LTI).

Role Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies.
• Influence developers, data analysts, and data scientists with expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Build using Python and Spark, leveraging open-source relational and NoSQL databases and cloud data warehousing platforms including Databricks and Snowflake.
• Stay current on data trends by experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring members of the data community.
• Partner with product managers and software engineers to deliver robust cloud-first data solutions that support experiences for millions of Americans.
• Independently design, build, and deliver cloud data solutions and applications with little or no support from supervisors or managers.
• Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability across platforms and pipelines.
• Design and build data pipelines and platforms focused on scalability, resilience, and operational efficiency to maintain performance as data and demands grow.
• Implement data security standards, including encryption at rest/transit and fine-grained access control, to support compliance with data privacy regulations.
• Serve as a data engineering ambassador by communicating technical concepts and data outcomes clearly to internal and external stakeholders to drive alignment.

Required Qualifications

• Bachelor’s Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering).
• At least 4 years of experience in application development (internship experience does not apply).
• 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 databases.

Technologies

• Python, Spark
• Databricks, Snowflake
• SQL, NoSQL, MongoDB, Cassandra, DynamoDB
• EMR, Glue, Airflow, Dagster
• Monte Carlo, Splunk, Redshift
• AWS, Microsoft Azure, Google Cloud
• Scala, Java

Preferred Qualifications

• 7+ years of experience in application development with demonstrated proficiency in Python, SQL, Scala, or Java.
• 4+ years of hands‑on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud).
• 4+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
• 4+ years of experience designing, implementing, and operating real-time or streaming data pipelines.
• 2+ years of experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (e.g., Airflow, Dagster).
• 4+ years of experience with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB).
• 4+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift).
• 2+ years of experience working in an Agile development environment.
• 2+ years of experience developing user-centric reusable data products.

Education

Bachelor’s Degree or higher in Computer Science or a related quantitative field.

Benefits

• Comprehensive, competitive, and inclusive set of health, financial, and other benefits that support total well-being.

Additional Information

• Expected application review window: minimum of 5 business days.
• No agencies please.
• Capital One will not sponsor a new applicant for employment authorization or provide immigration-related support for this position.
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
• Capital One promotes a drug‑free workplace.
• Pay range may vary for candidates hired in other locations.
• For technical support or questions about the recruiting process, email [e-mail].