Data Engineer 5 (Senior Manager, IC)-Risk Tech

Capital One’s Risk Tech group is hiring a Data Engineer 5 (Senior Manager, IC) based in McLean, VA (onsite). In this role, you will lead end-to-end, large-scale data engineering initiatives that help build and deploy AI-powered risk management solutions, working across modern data platforms and agile delivery teams.

You’ll combine full-stack data platform development with scalable pipeline design, mentoring, and cross-functional collaboration with GRC teams and agile partners. The focus is on delivering cloud-first capabilities and driving technical decisions that support performance, resilience, and operational efficiency as data volume and business demands grow.

What you’ll do

• Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies
• Influence a team of developers, data analysts, and data scientists with deep experience spanning machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Build with Python and Spark, leveraging open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake
• Partner with product managers and software engineers to deliver robust cloud-first data solutions that support experiences for millions of Americans focused on financial empowerment
• 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 improve code quality, maintainability, and reusability across platforms and pipelines
• Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency
• Serve as an ambassador for the data engineering team by communicating technical concepts and data outcomes clearly to internal and external stakeholders
• Lead large-scale, transformative data initiatives end to end, including critical architectural decisions and platform evaluations such as Snowflake versus Databricks
• Act as a force-multiplier through hands-on technical contribution, innovation, and mentoring to elevate peer and junior engineer skills

Required qualifications

• 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 of experience in distributed data
• 4+ years of experience with SQL
• 4+ years of 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, SQL
• Databricks, Snowflake, EMR, Glue, Airflow, Dagster
• Monte Carlo, Splunk
• AWS, Microsoft Azure, Google Cloud
• NoSQL, MongoDB, Cassandra, DynamoDB
• Redshift
• Java, Scala

Benefits

• Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• Comprehensive, competitive, and inclusive set of health, financial and other benefits that support total well-being

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 experience with demonstrated proficiency in Python, SQL, Scala, or Java
• 5+ years of hands-on experience designing, deploying, and operating data workloads in at least one public cloud environment (AWS, Microsoft Azure, or Google Cloud)
• 5+ years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
• 5+ years of 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 of experience working with unstructured or semistructured data using NoSQL databases (e.g., MongoDB, Cassandra, DynamoDB)
• 5+ years of experience designing and supporting data warehousing solutions (e.g., Snowflake, Redshift)
• 3+ years of experience working in an Agile development environment
• 3+ years of experience developing user-centric reusable data products

Salary

• McLean, VA: $229,900 - $262,400 (Data Engineer 5)
• Richmond, VA: $209,000 - $238,500 (Data Engineer 5)