Data Engineer 4

Capital One • McLean, VA

1d • Hybrid

About The Position

Capital One is seeking a Data Engineer passionate about combining data with emerging technologies to help drive a major transformation across the company. The role works across Agile teams to build, support, and deliver cloud-first data solutions and applications that support customer experiences and financial empowerment.

The Data Engineer independently designs and delivers cloud data solutions, establishes and enforces common engineering patterns, and builds scalable, resilient, secure data pipelines and platforms. The role also influences developers, data analysts, and data scientists; communicates technical concepts and data outcomes to stakeholders; and contributes to technology communities and mentoring. 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 count.
• 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 data pipeline design and development experience.
• 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 at least one public cloud environment: 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 a team of 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 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 supervisory support.
• Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across platforms and pipelines.
• Communicate technical concepts and data outcomes to internal and external stakeholders to foster alignment and shared understanding.
• 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, while supporting 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