Lead Software Engineer, Back End ( Enterprise Platforms Technology)(Apache Spark & Java)

Lead Software Engineer, Back End ( Enterprise Platforms Technology)(Apache Spark & Java) Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors, who love to solve real problems and meet real customer needs. We are seeking a forward-thinking Lead Back End Software Engineer to spearhead the architecture, development, and scaling of our core data infrastructure. As a Capital One Software Engineer, you’ll be on the forefront of driving a major transformation—leveraging traditional big data technologies alongside AI-native engineering workflows. Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. What You’ll Do: Architect & Build: Lead a portfolio of diverse technology projects and design robust, highly scalable data pipelines and microservices using Java, Apache Spark, Scala and Spring Boot. Scale for Billions: Engineer systems capable of ingesting, processing, and serving billions of customer data points with low latency, high availability, and strong data consistency. AI-Enhanced Development: Drive developer productivity by actively integrating AI coding assistants and autonomous agents (e.g., Claude Code, Co Pilot etc ) into daily development workflows, automated testing, and code refactoring. AI & LLM Integration: Design backend architectures and APIs that interface with AI/ML models and LLM endpoints for intelligent data enrichment and automated pipeline monitoring. Technical Leadership: Lead, mentor, and inspire a team of back-end and data engineers. Establish best practices for human-in-the-loop AI coding, conduct rigorous code reviews, and maintain high standards for system reliability. Cloud & Data Optimization: Leverage AWS services (EMR, Glue, lambda, step functions, S3, RDS, DynamoDB, Kinesis) to build cost-effective cloud architectures. Write optimized SQL queries with Open Source RDBMS and NoSQL databases and tune Spark jobs to minimize compute costs and maximize throughput. System Reliability: Implement robust monitoring, alerting, and automated pipelines to ensure data quality, pipeline integrity, and zero-downtime deployments.

Bachelor’s Degree At least 4 years of professional software engineering experience (Internship experience does not apply) At least 1 year experience with cloud computing (AWS, Microsoft Azure, Google Cloud) Preferred Qualifications: Master’s Degree 7 + years of professional engineering experience utilizing Java, Scala, Python, or Go 4 + years of experience with Advanced SQL and NoSQL database systems 3 +  years of hands-on cloud experience (AWS, Azure, or Google Cloud) 3 + years of experience working with various open source frameworks 2 + years of experience in Apache Spark performance tuning, specifically addressing memory configuration, data partitioning, and DAG optimization Proficiency in leveraging AI-native development tools (Claude Code, GitHub Copilot, Cursor, or OpenAI Canvas) to drive engineering velocity   At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the