Full-stack Engineer 4, Apache Spark, Java

Capital One

. Design, build, and maintain scalable data pipelines, distributed microservices, and full-stack applications using Java, Scala, Python, Go, Node.js, and TypeScript .

Posted 9/25/2026full-timeMcLean • Virginia • United StatesMid-LevelSenior💰 $179,400 - $225,100 per yearWebsite

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDistributed SystemsDockerDynamoDBGoogle Cloud PlatformJavaJavaScriptKubernetesMicroservicesNode.jsNoSQLPythonRDBMSScalaSparkSQLTypeScriptGo

About the role

Key responsibilities & impact

Design, build, and maintain scalable data pipelines, distributed microservices, and full-stack applications using Java, Scala, Python, Go, Node.js, and TypeScript
Engineer backend systems that ingest, process, and serve billions of customer data points with low latency, high availability, and strong data consistency
Partner with architects to define service boundaries, integration patterns, and reusable frameworks across cloud environments
Build cost-effective, high-throughput cloud architectures using AWS EMR, Glue, Lambda, Step Functions, S3, RDS, DynamoDB, and Kinesis
Write optimized SQL queries across open-source RDBMS and NoSQL systems
Tune Apache Spark jobs to minimize compute costs and maximize pipeline performance
Integrate AI coding assistants and autonomous tooling into development, testing, and refactoring workflows
Design backend architectures and APIs interfacing with AI/ML models and LLM endpoints
Lead, mentor, and inspire cross-functional backend, data, and full-stack engineering teams
Set technical standards for design, development, human-in-the-loop AI coding, and code reviews
Implement monitoring, alerting, and CI/CD pipelines for data quality, pipeline integrity, and zero-downtime deployments
Identify system bottlenecks, execute targeted refactoring, and reduce technical debt across distributed systems

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 software engineering; internship experience does not apply
At least 2 years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies
Preferred: Master's Degree in Computer Science or a related technical field
Preferred: 7+ years of professional software engineering experience coding in two or more languages
Preferred: 4+ years of experience with Advanced SQL and NoSQL database management systems
Preferred: 4+ years of experience creating synchronous and asynchronous APIs alongside open-source frameworks
Preferred: 3+ years of experience building and troubleshooting systems in cloud environments
Preferred: 3+ years of experience with CI/CD pipelines, Infrastructure as Code, automated testing frameworks, and Git-based version control
Preferred: 2+ years of hands-on experience in Apache Spark performance tuning
Preferred: 2 years of hands-on experience with Docker and Kubernetes
Preferred: 1+ year of experience leading cross-functional engineering initiatives, establishing coding standards, and mentoring engineers
Preferred: 1+ year of experience leveraging observability platforms to identify and eliminate performance bottlenecks
Proficiency with AI-native development tools and interactive AI environments, including Claude Code, GitHub Copilot, Cursor, and OpenAI Canvas
Capital One will not sponsor a new applicant for employment authorization or offer immigration-related support for this position

Benefits

Comp & perks

Performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being
Reasonable accommodation support
Equal opportunity and non-discrimination protections