Data Engineer 5 (Enterprise Platforms Technology)

Capital One is seeking a Data Engineer 5 to help lead a major transformation by building and supporting cloud-first data solutions and enterprise platforms. This role partners across teams to design, develop, test, implement, and operate data pipelines using modern data engineering technologies.

Onsite Location

New York, NY (onsite)

Compensation

• USD 250,800 - 286,200 per yearly
• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

Role Summary

In this position, you will influence technical direction and collaborate with Agile teams to deliver robust cloud-first data solutions. You will independently design, build, and deliver cloud data solutions and applications with limited supervision, while establishing common design patterns to support code quality, maintainability, and reusability across pipelines and platforms.

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions across full-stack development tools and technologies
• Influence developers, data analysts, and data scientists by leveraging expertise in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Use programming languages including Python and Spark, along with open-source relational and NoSQL databases and cloud data warehousing platforms such as Databricks and Snowflake
• Experiment with and learn new technologies, participate in internal and external technology communities, and mentor members of the data community
• Partner with product managers and software engineers to deliver cloud-first data solutions that support experiences helping millions of Americans achieve 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
• Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, including robust performance under increasing data volume and business demands
• Act as a force-multiplier through hands-on engineering, innovation, mentoring, and elevation of peer and junior engineering capability
• Serve as an ambassador for data engineering by communicating technical concepts and data outcomes clearly to internal and external stakeholders
• Lead and execute large-scale, end-to-end data initiatives, including critical architectural decisions and evaluating platform options (for example, Snowflake versus Databricks) based on technical and business requirements

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, or Scala
• 4+ years designing and developing data pipelines
• 2+ years designing end-to-end data solutions and data modeling using both relational and non-relational database systems

Technologies

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

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 environment (AWS, Microsoft Azure, or Google Cloud)
• 5+ years building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks
• 5+ years designing, implementing, and operating real-time or streaming data pipelines
• 3+ years of data observability experience (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 of experience working in an Agile development environment
• 3+ years of experience developing user-centric reusable data products

Additional Information

• Capital One will consider sponsoring a new qualified applicant for employment authorization for this position
• Expected to accept applications for a minimum of 5 business days
• No agencies please
• Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination
• Capital One promotes a drug-free workplace
• Accommodation contact: 1-800-304-9102 or [email protected]
• Technical support or recruiting process questions: [email protected]
• Capital One does not provide, endorse, or guarantee third-party products, services, educational tools, or other information available through this site
• Capital One Financial is made up of several different entities; positions posted in Canada, the United Kingdom, and the Philippines are for specific Capital One entities

Other Location Salary Ranges (Data Engineer 5)

• McLean, VA: USD 229,900 - 262,400
• Richmond, VA: USD 209,000 - 238,500
• San Francisco, CA: USD 250,800 - 286,200