Data Engineer 4 - ERM Transformation

Capital One is hiring a Data Engineer 4 to support ERM Transformation initiatives by building and deploying proprietary risk management solutions powered by advanced AI technology. The role focuses on cloud-first data solutions, scalable pipelines, and operational excellence in an Agile environment.

Role Summary

This position designs, builds, and operates cloud-based data solutions and pipelines with a strong emphasis on scalability, security, and operational efficiency. You will collaborate with product and engineering partners to deliver data capabilities that support financial empowerment at scale.

Key Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies.
• Provide technical influence to developers, data analysts, and data scientists with experience across machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Use Python and Spark, together with open-source relational and NoSQL databases and cloud data warehousing platforms including Databricks and Snowflake.
• Stay current with data engineering trends through experimentation, learning new technologies, participating in technology communities, and mentoring others.
• Partner with product managers and software engineers to deliver robust cloud-first data solutions.
• Independently design, build, and deliver cloud data solutions and applications with limited guidance 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 targeting scalability, resilience, and operational efficiency under increasing data volume and business demand.
• Implement data security standards, including encryption at rest/transit and fine-grained access control, to support compliance with data privacy regulations.
• Serve as an ambassador for the data engineering team by clearly communicating technical concepts and data outcomes to internal and external stakeholders.

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 database systems.

Technologies

• Python, Spark
• Databricks, Snowflake
• SQL
• Java, Scala
• NoSQL, relational databases
• Machine learning
• Distributed microservices
• Lakehouse architecture
• Agile
• Encryption at rest/transit
• Fine-grained access control

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 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 working 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.

Location and Compensation

Location: Richmond, VA (onsite)

Base Salary (annual): USD 179,400 - 204,700

This role may also be eligible to earn performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan.