Data Engineer 5 - Enterprise Risk Management

Capital One is hiring Data Engineers to help drive an Enterprise Risk Management transformation with cloud-first data platforms, pipelines, and scalable engineering patterns.

Responsibilities

• Partner with Agile teams to design, develop, test, implement, and support solutions across full-stack development tools and technologies
• Guide and influence developers, data analysts, and data scientists using expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Build with Python and Spark, using open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake
• Stay current on data engineering trends by experimenting with emerging technologies, contributing to internal and external communities, and mentoring the data community
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that support financial empowerment for millions of Americans
• Independently design, build, and deliver cloud data solutions and applications with limited direction from supervisors or managers
• Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability across pipelines and platforms
• Design and build data pipelines and platforms focused on scalability, resilience, and operational efficiency under growing volume and business demand
• Act as a force-multiplier by balancing hands-on engineering with innovation, mentoring, and elevating peers and junior engineers
• Lead end-to-end, large-scale data initiatives and make critical architectural decisions, including evaluating platforms such as Snowflake vs Databricks, based on technical and business requirements
• Serve as a data engineering ambassador by clearly communicating technical concepts and data outcomes to internal and external stakeholders

Requirements

• Bachelor’s degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• 6+ years of experience in application development (internship experience does not apply)
• 4+ years experience in distributed data
• 4+ years experience with SQL
• 4+ years programming with at least one of: Python, Java, Scala
• 4+ years designing and developing data pipelines
• 2+ years 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, AWS, Microsoft Azure, Google Cloud
• EMR, Glue, Airflow, Dagster
• Monte Carlo, Splunk
• MongoDB, Cassandra, DynamoDB
• Redshift

Preferred Qualifications

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

Benefits

• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being

Compensation and Location

• McLean, VA (onsite): $229,900 - $262,400 per year for Data Engineer 5
• Richmond, VA: $209,000 - $238,500 per year for Data Engineer 5
• Expected to accept applications for a minimum of 5 business days
• No agencies please