Data Engineer 4 (Manager, IC)

Capital One • Richmond, VA

2d • $179,400 - $204,700

About The Position

Capital One is seeking a Data Engineer 4 to build and deliver cloud-first data solutions and applications as part of a major technology transformation. The role collaborates with Agile teams, product managers, software engineers, data analysts, and data scientists to create solutions that support customer experiences and financial empowerment. It involves independently designing and delivering cloud data applications, influencing other technical contributors, and communicating technical concepts and data outcomes to stakeholders.

The position focuses on scalable, resilient, and operationally efficient data pipelines and platforms. The engineer establishes and enforces common design patterns for quality, maintainability, and reusability, and implements data security controls such as encryption and fine-grained access control. The role also involves working with Python and Spark, relational and NoSQL databases, and cloud data warehousing platforms such as Databricks and Snowflake. The position supports experimentation with emerging technologies, participation in technology communities, and mentoring within the data community.

The role is based on salary information provided for Richmond, Virginia; the posting does not specify a work arrangement. Capital One states that this role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. The company does not sponsor new applicants for employment authorization or provide immigration-related support for this position.

Requirements

• Bachelor's degree or higher in Computer Science or a related quantitative field, such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
• At least 4 years of application development experience; internship experience does not apply.
• At least 2 years of experience in distributed data.
• At least 2 years of SQL experience.
• At least 2 years of experience with one programming language: Python, Java, or Scala.
• At least 2 years of data pipeline design and development experience.
• At least 1 year of experience in data modeling and designing end-to-end data solutions using relational and non-relational database systems.

Nice To Haves

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

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions.
• Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Use programming languages such as Python and Spark, relational and NoSQL databases, and cloud-based data warehousing platforms such as Databricks and Snowflake.
• Keep current with data technology trends, experiment with and learn new technologies, participate in technology communities, and mentor members of the data community.
• Collaborate with product managers and software engineers to deliver cloud-first data solutions.
• Independently design, build, and deliver cloud data solutions and applications with little or no supervisor or manager support.
• Architect and enforce common data engineering design patterns that promote code quality, maintainability, and reusability across platforms and pipelines.
• Communicate technical concepts and data outcomes to internal and external stakeholders to build alignment and shared understanding.
• Design and build scalable, resilient, and operationally efficient data pipelines and platforms.
• Implement data security standards, including encryption at rest and in transit and fine-grained access control, to support compliance with data privacy regulations.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior