Data Engineer

Capital One

. Collaborate across Agile teams to design, develop, test, implement, and support technical solutions .

Posted 9/29/2026full-timeWilmington • Virginia • United StatesMid-LevelSenior💰 $179,400 - $225,100 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing cloud-based data solutions, utilizing Python, SQL, and data pipeline development. Proficient in architecting scalable data systems and ensuring data security while collaborating effectively across Agile teams.

Highest-signal resume keywords

Python DevelopmentSQL ProficiencyData Pipeline DesignCloud Data SolutionsData Engineering Design Patterns

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Application DevelopmentData ModelingDistributed DataData WarehousingData Security StandardsMachine LearningMicroservices ArchitectureNoSQL DatabasesRelational DatabasesData Pipeline Development

Soft Skills

CollaborationMentoringCommunication

Tools & Technologies

DatabricksSnowflakeAWSMicrosoft AzureGoogle CloudEMRSparkGlueAirflowMonte Carlo

Industry Keywords

Agile DevelopmentData TrendsData CommunityStreaming Data PipelinesUser-Centric Data Products

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureCassandraCloudDynamoDBJavaMicroservicesMongoDBNoSQLPythonScalaSparkSplunkSQL

About the role

Key responsibilities & impact

Collaborate across Agile teams to design, develop, test, implement, and support technical solutions
Influence developers, data analysts, and data scientists across machine learning, distributed microservices, lakehouse architecture, and full-stack systems
Use Python and Spark, open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and Snowflake
Stay current with data trends, experiment with new technologies, participate in technology communities, and mentor data community members
Collaborate with product managers and software engineers to deliver cloud-first data solutions
Independently design, build, and deliver cloud data solutions and applications
Architect and enforce data engineering design patterns for code quality, maintainability, and reusability
Communicate technical concepts and data outcomes to internal and external stakeholders
Design and build scalable, resilient, and operationally efficient data pipelines and platforms
Implement data security standards including encryption and fine-grained access control

Requirements

What you’ll need

Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 4 years of experience in application development; internship experience does not apply
At least 2 years of experience in distributed data
At least 2 years of experience with SQL
At least 2 years of experience with 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
New applicants requiring employment authorization or immigration-related employer support are not sponsored
Preferred: 7+ years of application development experience
Preferred: 4+ years designing, deploying, and operating data workloads in a public cloud environment (AWS, Microsoft Azure, or Google Cloud)
Preferred: 4+ years building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
Preferred: 4+ years designing, implementing, and operating real-time or streaming data pipelines
Preferred: 2+ years with data observability or orchestration tools such as Monte Carlo, Splunk, Airflow, or Dagster
Preferred: 4+ years with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB
Preferred: 4+ years designing and supporting data warehousing solutions such as Snowflake or Redshift
Preferred: 2+ years in an Agile development environment
Preferred: 2+ years developing user-centric reusable data products

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being
Reasonable accommodations for applicants who require them