Data Engineer 4

Capital One • McLean, VA

3d • $179,400 - $245,600 • Hybrid

About The Position

Capital One is seeking a Data Engineer 4 to build and pioneer technology solutions, combine data with emerging technologies, and help drive a major transformation. The position works across Agile teams to develop and support cloud-first data solutions and applications that support customer experiences and financial empowerment.

The role independently designs and delivers cloud data solutions, establishes data engineering patterns for quality and reuse, and builds scalable, resilient, and operationally efficient data pipelines and platforms. It also applies data security standards, including encryption and fine-grained access controls, and communicates technical concepts and outcomes to internal and external stakeholders. This is a hybrid position subject to Capital One’s policy on required on-site presence at the designated office location.

Requirements

• Bachelor’s degree or higher in Computer Science or a related quantitative field, such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
• At least 4 years of application development experience; internship experience does not apply.
• At least 2 years of experience in distributed data.
• At least 2 years of SQL experience.
• 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 relational and non-relational database systems.

Nice To Haves

• 7 or more years of application development experience, with demonstrated proficiency in Python, SQL, Scala, or Java.
• 4 or more years of hands-on experience designing, deploying, and operating data workloads in a public cloud environment such as AWS, Microsoft Azure, or Google Cloud.
• 4 or more years of experience building or supporting distributed data or compute workloads using tools such as EMR, Spark, Glue, or Databricks.
• 4 or more years of experience designing, implementing, and operating real-time or streaming data pipelines.
• 2 or more years of experience with data observability tools such as Monte Carlo or Splunk, or data orchestration tools such as Airflow or Dagster.
• 4 or more years of experience working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB.
• 4 or more years of experience designing and supporting data warehousing solutions such as Snowflake or Redshift.
• 2 or more years of experience working in an Agile development environment.
• 2 or more years of experience developing user-centric reusable data products.

Responsibilities

• Collaborate with 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 working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Use technologies including Python, Spark, open-source relational and NoSQL databases, Databricks, and Snowflake.
• Stay current with data technology trends, experiment with and learn new technologies, participate in technology communities, and mentor members of the data community.
• Collaborate with product managers and software engineers to deliver cloud-first data solutions.
• Independently design, build, and deliver cloud data solutions and applications with little or no supervisor or manager support.
• Architect and enforce common data engineering design patterns to support code quality, maintainability, and reuse across platforms and pipelines.
• Communicate technical concepts and data outcomes clearly to internal and external stakeholders.
• Design and build scalable, resilient, and operationally efficient data pipelines and platforms that perform reliably as data volumes and business demands grow.
• Implement data security standards, including encryption at rest and in transit and fine-grained access control, to support compliance with data privacy regulations.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior