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# Senior Java Developer, Credit Risk & Data Engineering

- **Company:** Business Integration Partners USA Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Data Analysis, Applications Architecture, Application Integration Architecture, Automation of Tests, Big Data, Cloudera Impala, Software Quality, Code Review, Encodings, Computer Programming, Databases, Continuous Integration, Information Engineering, Data Transformation, 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, Query Optimization, Raw Data, Reference Data, Standard Sql, Reverse Engineering, Scala (Programming Language), Service-Oriented Architecture, Software Engineering, SQL Databases, Data Streaming, Enterprise Data Management, Parquet, Data Processing, Multithreading, Enterprise Software Applications, Cloud Platform System, Concurrency, Apache Spark, Spring-boot, Caching, Electronic Medical Records, Backend, Git, Containerization, Pyspark, Solid Principles, Information Technology, Apache Kafka, Data Management, Restful APIs, Code Restructuring, Data Pipelines, Microservices
- **Published:** September 20, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c985d27a3ad7d3e6

## 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.

· Strong hands-on programming experience with Java and working knowledge of Python and/or Scala for data-intensive application development.

· Strong production experience with Apache Spark, including development and optimization of large-scale distributed data-processing workloads.

· Hands-on experience working with Parquet and large-scale columnar datasets, including partitioning, schema management, compression, encoding, and query/performance optimization.

· Strong SQL skills and experience querying, transforming, reconciling, and analyzing large datasets.

· Experience designing and building scalable data pipelines, transformation frameworks, aggregation processes, and batch/distributed processing solutions.

· Strong understanding of distributed computing, multi-threading/concurrency, software design principles, data structures, algorithms, and application architecture.

· Experience tuning large-scale data workloads, including Spark joins, partitioning, caching, data skew, memory/resource utilization, and throughput.

· Experience designing, developing, and integrating backend services, APIs, and enterprise application components.

· Experience working across the full software development lifecycle, including requirements, design, development, testing, deployment, and production support.

· Strong debugging, performance optimization, data-quality analysis, and problem-solving skills.

· Experience working directly with business, risk, quantitative, and technology stakeholders and translating complex requirements into technical solutions.

· Strong written and verbal communication skills with the ability to operate effectively in a client-facing consulting environment.

· Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline, or equivalent professional experience.

Preferred Qualifications:

· Experience developing technology solutions supporting Credit Risk, Market Risk, regulatory risk, or enterprise trade/risk data platforms.

· Knowledge of financial data domains including trades, positions, sensitivities, reference data, counterparty/exposure data, RWA, VaR, or related risk measures.

· Experience with Big Data ecosystems and technologies such as Hive, HDFS, Iceberg, HBase, Impala, Kafka, Dremio, EMR, or comparable platforms.

· Experience building both batch and streaming data-processing solutions for real-time and historical financial data.

· Experience with Java, Python, Scala, Spark/PySpark, SQL, Spring Boot, and modern backend development frameworks.

· Experience with cloud-based data platforms, particularly AWS and EMR, as well as containerization and modern CI/CD practices.

· Experience with performance engineering across Spark, Java, SQL, and large-scale data storage platforms.

· Experience modernizing, refactoring, or reverse engineering large legacy technology and data platforms.

· Experience with data quality, reconciliation, lineage, metadata management, and auditability in regulated environments.

· Experience working within Tier 1 investment banks or other large financial institutions.

· Prior management consulting experience, preferably with a leading consulting or technology services organization.

· Exposure to AI/ML techniques or agentic engineering tooling applied to data or software engineering workflows is beneficial.

· Demonstrated ability to work independently and take ownership of complex technical problems from initial analysis through implementation.

Technical Skills:

· Programming Languages: Java, Python, Scala, SQL

· Big Data / Distributed Processing: Apache Spark, PySpark, Hive, HDFS, Iceberg, Parquet, Kafka, and comparable distributed data technologies

· Backend Development: Java, Spring Boot, REST APIs, microservices, service-oriented architectures, batch and streaming processing

· Data Engineering: Large-scale data pipelines, data transformation and enrichment, partitioning, aggregation, reconciliation, columnar storage, data quality and lineage

· Performance Engineering: Spark optimization, repartitioning, salting, broadcast joins, caching, concurrency, query tuning, compression and throughput optimization

· Architecture & Platforms: Distributed systems, scalable data-processing architecture, AWS/EMR, enterprise data platforms and application integration

· Development Practices: Git, CI/CD, automated testing, code reviews, Agile software development

· Capital Markets & Risk: Credit Risk, Market Risk, trade and position data, sensitivities, reference data, risk calculations, financial data processing and reporting, * Do you have hands-on production experience developing and optimizing large-scale data processing solutions using Apache Spark/PySpark?

 * Do you have software/data engineering experience within Credit Risk, Market Risk, or Capital Markets, using Java?
 * Do you have hands-on experience working with Parquet and processing, transforming, and aggregating large volumes of financial, trade, or risk data?
 * Do you have hands-on experience designing and optimizing batch and/or streaming data pipelines for large-scale enterprise datasets?
 * Do you have experience with Spark performance optimization techniques such as partitioning/repartitioning, broadcast joins, caching, and data skew management?
 * Do you require a work authorization sponsorship to work in this country now or in the future?

Work Location: Hybrid remote in New York, NY 10041

## 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., · Design, develop, enhance, and support scalable software and data-processing solutions supporting Capital Markets, Credit Risk, Market Risk, and related Financial Services functions.

· Own development activities across the full software development lifecycle, from requirements analysis and technical design through development, testing, deployment, and production support.

· Build and optimize large-scale batch and, where required, streaming data pipelines using Apache Spark and related distributed data-processing technologies.

· Design scalable backend services, processing engines, APIs, and integration components using Java, Python, Scala, and/or comparable technologies.

· Ingest, transform, enrich, aggregate, reconcile, and analyze large volumes of trade, position, sensitivity, reference, counterparty, and risk data.

· Work with Parquet and other columnar/table storage formats, applying effective partitioning, compression, encoding, compaction, and data-access strategies to improve performance.

· Optimize Spark workloads using techniques such as repartitioning, salting, broadcast joins, caching, and other performance-tuning approaches.

· Partner directly with Credit Risk, Market Risk, front-office, quantitative, data, architecture, and technology stakeholders to understand requirements and develop appropriate solutions.

· Translate complex risk, business, and data requirements into robust technical designs and scalable processing frameworks.

· Analyze, troubleshoot, refactor, and optimize existing applications, data pipelines, and large or complex codebases.

· Improve application and data-platform performance, scalability, maintainability, reliability, throughput, and overall code quality.

· Develop solutions with appropriate data quality controls, reconciliation, lineage, transparency, and auditability for regulated financial environments.

· Participate in architecture and technical design discussions and provide recommendations regarding data models, storage patterns, processing frameworks, and implementation approaches.

· Perform code reviews and contribute to software engineering and data engineering standards and development best practices.

· Diagnose and resolve complex application, integration, data, Spark, database, and production issues.

· Collaborate across globally distributed development, risk, data, and business teams.

· Communicate technical concepts clearly to both technical and non-technical client stakeholders.


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