Data Engineer 4 (Manager IC) Risk Tech

Capital One • Richmond, VA

9d

About The Position

Capital One is seeking a Data Engineer to help transform risk management through technology. The role is part of Risk Tech, which builds data-driven tools that use machine learning to prevent risk and automatically detect issues before they affect customers, the business, or communities. The engineer will design, build, deliver, and support cloud-first data solutions and applications, working across Agile teams and with product managers, software engineers, developers, analysts, and data scientists. The work includes developing scalable and resilient pipelines and platforms; applying shared engineering patterns; ensuring code quality, maintainability, and reuse; and implementing data security controls. The role also involves communicating technical concepts and data outcomes to stakeholders, staying current with technology trends, participating in technical communities, and mentoring members of the data community. The position requires independent delivery of cloud data solutions with little or no supervisory support. Listed full-time annual salary ranges vary by location: McLean, Virginia, $197,300–$225,100; New York, New York, $215,200–$245,600; and Richmond, Virginia, $179,400–$204,700. The role is also eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One does not provide new employment authorization sponsorship or related immigration 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 a public cloud environment such as 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 across 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, open-source relational and NoSQL databases, and cloud-based data warehousing platforms such as Databricks and Snowflake.
• Keep current with data trends and new technologies, participate in internal and external 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 support from supervisors or managers.
• Architect and enforce common data engineering design patterns to promote code quality, maintainability, and reusability across platforms and pipelines.
• Communicate technical concepts and data outcomes clearly to internal and external stakeholders.
• 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 controls, to support compliance with data privacy regulations.

Benefits

• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.
• Eligible 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