Data Engineer 4 (Manager IC) - Modeling & Architecture

Capital One • Richmond, VA

3d

About The Position

Capital One is seeking a Data Engineer to help drive a major technology transformation by building cloud-first data solutions and applications. The role works across Agile teams and collaborates with product managers, software engineers, data analysts, and data scientists to deliver scalable data platforms and pipelines that support customer experiences.

The position independently designs, builds, and delivers cloud data solutions, establishes and enforces data engineering design patterns, and focuses on code quality, maintainability, reusability, resilience, scalability, and operational efficiency. It also applies data security standards, including encryption and fine-grained access controls, and communicates technical concepts and data outcomes to stakeholders. The engineer is expected to keep current with data technologies, participate in technology communities, and mentor others.

The position requires a bachelor's degree or higher in computer science or a related quantitative field, along with experience in application development, distributed data, SQL, programming, data pipelines, and data modeling. Preferred experience includes cloud platforms, distributed and streaming workloads, data observability or orchestration, NoSQL, data warehousing, Agile development, and reusable data products.

The role is eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives. Capital One also offers a comprehensive benefits package; eligibility varies by employment status and management level. Capital One will not provide new employment authorization sponsorship or other immigration-related support for this position.

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 count.
• At least 2 years of experience in distributed data.
• At least 2 years of experience with SQL.
• 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 experience in data architecture or data modeling.
• 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 across Agile teams to design, develop, test, implement, and support technical solutions.
• Influence developers, data analysts, and data scientists working with machine learning, distributed microservices, lakehouse architecture, and full-stack systems.
• Use programming languages such as Python and Spark, open-source relational and NoSQL databases, and cloud data warehousing platforms such as Databricks and Snowflake.
• Stay current with data trends and 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 supervisory support.
• Architect and enforce common data engineering design patterns to promote code quality, maintainability, and reusability 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.
• 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.
• Performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives.

What This Job Offers

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