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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Java Developer, Credit Risk & Data Engineering - **Company:** Business Integration Partners (bip) - **Location:** United States - **Experience:** Expert - **Salary:** $150,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Applications Architecture, Big Data, Cloudera Impala, Encodings, Computer Programming, Continuous Integration, Data Structures, Database Queries, Software Debugging, Distributed Computing Environment, Distributed Data Store, Distributed Systems, Hadoop Distributed File System, Apache HBase, Apache Hive, Python (Programming Language), Machine Learning, Meta-Data Management, Performance Tuning, Reference Data, Reverse Engineering, Scala (Programming Language), Software Engineering, SQL Databases, Data Streaming, Systems Integration, Parquet, Data Processing, Multithreading, Enterprise Software Applications, Cloud Platform System, Concurrency, Apache Spark, Spring-boot, Caching, Backend, Agentic-AI, Containerization, Pyspark, Solid Principles, Information Technology, Apache Kafka, Data Management, Code Restructuring, Data Pipelines - **Published:** October 6, 2026 - **Apply:** https://www.thejobnetwork.com/job/c88a528c-2f5b-4a61-a487-4d9ec54d3510/senior-java-developer-credit-risk-data-engineering ## About the Role The successful candidate will combine strong software engineering fundamentals with deep hands-on experience in large-scale financial data processing. The role places particular emphasis on Java, Apache Spark, SQL, Parquet and distributed data technologies used to ingest, enrich, aggregate, optimize, and deliver trade, position, sensitivity, reference, and risk data., Candidates should bring strong analytical and problem-solving capabilities, experience working with complex financial data platforms, and the communication skills necessary to partner with Credit Risk, Market Risk, front-office, quantitative, architecture, and technology stakeholders in a client-facing consulting environment., * 8+ years of professional software engineering, data engineering, or application development experience, preferably within Financial Services, Capital Markets, Risk, or another complex enterprise environment. \n * Strong hands-on programming experience with Java and working knowledge of Python and/or Scala for data-intensive application development. \n * Strong production experience with Apache Spark, including development and optimization of large-scale distributed data-processing workloads. \n * Hands-on experience working with Parquet and large-scale columnar datasets, including partitioning, schema management, compression, encoding, and query/performance optimization. \n * Strong SQL skills and experience querying, transforming, reconciling, and analyzing large datasets. \n * Experience designing and building scalable data pipelines, transformation frameworks, aggregation processes, and batch/distributed processing solutions. \n * Strong understanding of distributed computing, multi-threading/concurrency, software design principles, data structures, algorithms, and application architecture. \n * Experience tuning large-scale data workloads, including Spark joins, partitioning, caching, data skew, memory/resource utilization, and throughput. \n * Experience designing, developing, and integrating backend services, APIs, and enterprise application components. \n * Experience working across the full software development lifecycle, including requirements, design, development, testing, deployment, and production support. \n * Strong debugging, performance optimization, data-quality analysis, and problem-solving skills. \n * Experience working directly with business, risk, quantitative, and technology stakeholders and translating complex requirements into technical solutions. \n * Strong written and verbal communication skills with the ability to operate effectively in a client-facing consulting environment. \n * Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent professional experience. \n, * Experience developing technology solutions supporting Credit Risk, Market Risk, regulatory risk, or enterprise trade/risk data platforms. \n * Knowledge of financial data domains including trades, positions, sensitivities, reference data, counterparty/exposure data, RWA, VaR, or related risk measures. \n * Experience with Big Data ecosystems and technologies such as Hive, HDFS, Iceberg, HBase, Impala, Kafka, Dremio, EMR, or comparable platforms. \n * Experience building both batch and streaming data-processing solutions for real-time and historical financial data. \n * Experience with Java, Python, Scala, Spark/PySpark, SQL, Spring Boot, and modern backend development frameworks. \n * Experience with cloud-based data platforms, particularly AWS and EMR, as well as containerization and modern CI/CD practices. \n * Experience with performance engineering across Spark, Java, SQL, and large-scale data storage platforms. \n * Experience modernizing, refactoring, or reverse engineering large legacy technology and data platforms. \n * Experience with data quality, reconciliation, lineage, metadata management, and auditability in regulated environments. \n * Experience working within Tier 1 investment banks or other large financial institutions. \n * Prior management consulting experience, preferably with a leading consulting or technology services organization. \n * Exposure to AI/ML techniques or agentic engineering tooling applied to data or software engineering workflows is beneficial. \n * Demonstrated ability to work independently and take ownership of complex technical problems from initial analysis through implementation. ## Description We are seeking an experienced Senior Java Developer - Credit Risk & Data Engineering to design, develop, and enhance scalable software and data-processing solutions supporting Capital Markets and Credit Risk functions at leading financial institutions.