Data Engineer 5 - Enterprise Risk Management

Capital One is hiring Data Engineers to help lead a cloud-first transformation for Enterprise Risk Management in McLean, VA.

Responsibilities

• Partner with Agile teams to design, build, test, implement, and support full-stack development solutions
• Provide technical influence across developers, data analysts, and data scientists with expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Develop using Python and Spark and work with open-source relational and NoSQL databases
• Build and deliver cloud data solutions using platforms such as Databricks and Snowflake
• Stay current on data engineering trends by experimenting with new technologies, contributing to technology communities, and mentoring others
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions for large-scale customer impact
• Independently design, build, and deliver cloud data applications with minimal support from supervisors or managers
• Architect and enforce common data engineering design patterns to improve code quality, maintainability, and reusability
• Create scalable, resilient, and operationally efficient data pipelines and platforms that perform under increasing volumes and demands
• Act as a force-multiplier through hands-on delivery, innovation, and skill growth for peers and junior engineers
• Lead end-to-end, large-scale transformative data initiatives, including architecture decisions (for example, Snowflake vs Databricks) based on technical and business needs
• Communicate technical concepts and data outcomes clearly 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, or Scala
• 4+ years designing and developing data pipelines
• 2+ years designing data models and end-to-end solutions using both relational and non-relational databases

Technologies

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

Benefits

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

Preferred Qualifications

• Master’s Degree in Computer Science or 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 environment (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 of experience in data observability (e.g., Monte Carlo, Splunk) or data orchestration tools (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 working in an Agile development environment
• 3+ years developing user-centric reusable data products

Salary / Incentives / Location

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