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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Java Data Engineer - **Company:** NTT DATA, Inc. - **Location:** Nashville, TN, United States - **Experience:** Expert - **Salary:** $104,000.0 - $135,200.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Amazon Web Services, Component-Based Software Engineering, Code Review, Databases, Computer Engineering, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Relational Databases, Amazon DynamoDB, Github, Enterprise Messaging Systems, Oracle Databases, Oracle (Applications), Release Management, Software Tools, Cloud Services, Standard Sql, Software Engineering, PL-SQL, SQL Databases, Data Streaming, Systems Integration, Enterprise Data Management, Data Logging, Data Processing, Enterprise Software Applications, Real Time Systems, Snowflake, Kubernetes, Information Technology, Deployment Automation, IBM UrbanCode Deploy, Real Time Data, Apache Kafka, Database Replication, Restful APIs, Splunk, Software Version Control, Data Pipelines, Docker, Jenkins - **Published:** September 10, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0ba63ea9a881f407 ## About the Role * Overall Experience: 7+ years of combined data engineering and software engineering experience. * Java: 5+ years of experience developing Java-based data processing, pipeline, database integration, or messaging solutions. * PL/SQL: 5+ years of experience developing complex PL/SQL queries, packages, procedures, functions, and database components. * Oracle: 4+ years of experience developing or supporting enterprise data solutions using Oracle relational databases. * + SQL and Relational Databases: 4+ years of experience writing complex SQL and working with relational database platforms. * Data Integration: 4+ years of experience integrating data across databases, APIs, files, enterprise applications, or messaging platforms. * Data Pipelines: 4+ years of experience designing, building, testing, deploying, and supporting enterprise data pipelines. * Kafka: 3+ years of hands-on experience using Kafka for messaging, streaming, or enterprise data movement. * Data Warehousing and Modeling: 3+ years of experience applying data warehousing, logical or physical data modeling, and batch or real-time processing concepts. * RESTful APIs: 3+ years of experience developing, integrating, or supporting RESTful APIs for data integration. * Version Control and CI/CD: 3+ years of experience using GitHub, Jenkins, uDeploy, or comparable source control and continuous integration and deployment tools. * Docker: 2+ years of experience packaging, deploying, or supporting data or application components using Docker. * Production Monitoring: 2+ years of experience monitoring and troubleshooting production systems using Splunk or a comparable logging and monitoring platform. * Stakeholder Collaboration: 4+ years of experience working with clients, business stakeholders, or cross-functional technical teams to translate requirements into delivered solutions. * Degree: Bachelor's or Master's degree in Computer Science, Computer Engineering, or a related technology field. Nice to Have: * Experience with Kubernetes or another container orchestration platform. * Experience developing or supporting solutions on AWS or another public cloud platform. * Experience using Python for data processing, pipeline development, or automation. * Familiarity with Snowflake, DynamoDB, or another cloud-native data platform. * Experience with data replication, performance engineering, or resilient system design. * Experience supporting financial services, finance, risk, or compliance data. * Experience leading technical discussions, conducting code reviews, or coaching other engineers. * Ability to explain technical concepts to nontechnical audiences. * Excellent written and verbal communication, problem-solving, organizational, and presentation skills. * Ability to operate independently, work comfortably with ambiguity, and adapt quickly to new technologies and changing priorities. ## Description We are seeking a Senior Data Engineer to design, develop, and support enterprise data pipelines and data integration solutions using Java, PL/SQL, Oracle, and Kafka. In this role, you will build reliable batch and real-time data workflows, integrate data across enterprise platforms, and work closely with financial services clients and engineering teams to translate complex requirements into scalable data solutions. Design, build, test, deploy, and support enterprise data pipelines that source, transform, and deliver data based on business and technical requirements. * Develop Java-based data processing and integration components that connect Oracle databases, Kafka messaging, APIs, files, and enterprise applications. * Develop and optimize complex PL/SQL queries, packages, procedures, functions, and other Oracle database components supporting data movement and transformation. * Use Kafka to support event-driven data movement, messaging, streaming, and near-real-time processing. * Apply relational database, data warehousing, logical and physical data modeling, and data integration practices to deliver reliable and reusable data solutions. * Monitor, troubleshoot, and resolve pipeline, database, performance, and production-processing issues using tools such as Splunk. * Use GitHub, Jenkins, uDeploy, Docker, and related engineering tools to support source control, continuous integration, deployment, and release management. * Collaborate within a pod of four or more data engineers, contributing to solution design, code reviews, testing, deployment, production support, and shared delivery objectives. * Partner with multiple client and stakeholder groups to understand requirements, communicate technical concepts, manage priorities, and deliver solutions in a consultative manner. * Independently identify knowledge gaps, learn new technologies, and adapt existing engineering skills to evolving platforms, tools, and business needs. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Bringing AI Model Testing and Prompt Management to Your Codebase with GitHub Models](https://www.wearedevelopers.com/videos/1536-bringing-ai-model-testing-and-prompt-management-to-your-codebase-with-github-models) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [What’s the Difference between a Junior, Mid, and Senior Developer?](https://www.wearedevelopers.com/magazine/238-what-s-the-difference-between-a-junior-mid-and-senior-developer)