Data Engineer

Capital One

. Collaborate across Agile teams to design, develop, test, implement, and support technical solutions using full-stack development tools and technologies .

Posted 9/22/2026full-timeMcLean • Virginia • United StatesMid-LevelSenior💰 $229,900 - $262,400 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in full-stack development, data engineering, and cloud-based solutions, with a strong focus on Python, SQL, and data pipeline design. Proven ability to mentor teams, lead data initiatives, and communicate complex technical concepts effectively.

Highest-signal resume keywords

Full-Stack DevelopmentData EngineeringPython ProgrammingSQL ProficiencyCloud Data Solutions

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLJavaScalaData Pipeline DesignData ModelingMachine LearningDistributed DataNoSQL DatabasesData Warehousing

Soft Skills

CollaborationMentoringCommunicationInfluencingProblem-Solving

Tools & Technologies

DatabricksSnowflakeAWSMicrosoft AzureGoogle CloudEMRSparkGlueAirflowMonte Carlo

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMaster's Degree in Computer Science

Industry Keywords

Agile DevelopmentData SolutionsCloud ComputingData Engineering Design PatternsReal-Time Data Pipelines

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 using full-stack development tools and technologies
Influence developers, data analysts, and data scientists working with 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 professionals
Collaborate with product managers and software engineers to deliver robust cloud-first data solutions
Independently design, build, and deliver cloud data solutions and applications
Architect and enforce common 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
Mentor and elevate peers and junior engineers while contributing hands-on technical expertise
Lead large-scale data initiatives end to end, making architectural decisions and evaluating platforms such as Snowflake and Databricks

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 6 years of experience in application development; internship experience does not apply
At least 4 years of experience in distributed data
At least 4 years of experience with SQL
At least 4 years of programming experience with Python, Java, or Scala
At least 4 years of experience designing and developing data pipelines
At least 2 years of experience in data modeling and designing end-to-end data solutions using relational and non-relational database systems
Capital One will consider sponsoring a new qualified applicant for employment authorization
Preferred: Master's Degree in Computer Science or a related field
Preferred: 8+ years of experience in data engineering
Preferred: 4+ years of data modeling experience
Preferred: 9+ years of application development experience with Python, SQL, Scala, or Java
Preferred: 5+ years of experience designing, deploying, and operating data workloads in AWS, Microsoft Azure, or Google Cloud
Preferred: 5+ years building or supporting distributed data or compute workloads using EMR, Spark, Glue, or Databricks
Preferred: 5+ years designing, implementing, and operating real-time or streaming data pipelines
Preferred: 3+ years working with data observability or data orchestration tools such as Monte Carlo, Splunk, Airflow, or Dagster
Preferred: 5+ years working with unstructured or semistructured data using NoSQL databases such as MongoDB, Cassandra, or DynamoDB
Preferred: 5+ years designing and supporting data warehousing solutions such as Snowflake or Redshift
Preferred: 3+ years working in an Agile development environment
Preferred: 3+ years developing user-centric reusable data products

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
Comprehensive, competitive health, financial, and other benefits supporting total well-being
Reasonable accommodation support for applicants who require it