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# J2Ee Developer

- **Company:** TSR, Inc
- **Location:** Lutz, FL, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Cloudera Impala, Software Quality, Databases, Continuous Integration, Couchbase Servers, Memory Management, Java Platform Enterprise Edition (J2EE), Github, Apache Hadoop, Apache Hive, Java Database Connectivity, PostgreSQL, MongoDB, MySQL, Neo4j, NoSQL, Object-Oriented Software Development, Oracle (Applications), Performance Tuning, Microsoft Copilot, Software Engineering, SQL Databases, Multithreading, Enterprise Software Applications, Apache Spark, Agentic-AI, Claude, Software Version Control, Data Pipelines
- **Published:** October 9, 2026
- **Apply:** https://www.disabledperson.com/jobs/75919435-j2ee-developer

## About the Role

* 7+ years of experience in software development, specifically Core Java & Java 8 concepts (OOP, OOD, Collections, Exception Handling, JDBC, Multithreading, Streams, Lamda Expressions, Functional Interfaces, etc.).
 * 5+ years of experience in SQL/NoSQL database management systems (Oracle, MySQL, Postgres, MongoDB, Couchbase, Neo4j)
 * 3+ years of experience leading/owning software development projects from beginning to end with multiple team members.
 * Experience working in financial market and credit risk enterprise software systems including, but not limited to, scenario analysis and stress testing.
 * Experience with GitHub, Tekton, Harness, and other CI/CD pipeline technologies.
 * Ability to work in a fast-paced TechFin environment.
 * Experience with agentic AI tools (Devin, Claude, or Copilot)

## Description

* Design, develop, optimize, and maintain scalable data pipelines for processing and analyzing large scale financial data built on Core Java
 * Lead projects for developing batch pipeline processes for credit risk analytics including, but not limited to, stress loss (GSST, CCAR) and expected credit loss (CECL, IFRS9, ICAAP)
 * Ensure the efficient storage of and retrieval of all risk data in our big data platform systems (Hadoop, Hive, Impala, Spark, etc.)
 * Implement best practices for spark performance tuning including, but not limited to, partitioning, caching, and memory management.
 * Maintain code quality through high-efficiency testing, CI/CD pipelines (Tekton, Harness), and version control (GitHub).