Senior Java Developer, Credit Risk & Data Engineering

Company Overview:

Business Integration Partners (BIP) is Europe’s fastest growing digital consulting company and are on track to reach the Top 20 by 2030, with an expanding global footprint in the US (New York, Charlotte, Chicago, and Houston). Operating at the intersection of business and technology, we design, develop, and deliver sustainable solutions at pace and scale, creating greater value for our customers, employees, shareholders, and society.

BIP specializes in high-impact consulting services across multiple industries with 6,000 employees worldwide. Our Financial Services business serves Capital Markets, Insurance and Payments verticals, supplemented with Data & AI, Cybersecurity, Risk & Compliance, Change Management and Digital Transformation practices. We integrate deep industry expertise with business, technology, and quantitative disciplines to deliver high-impact results for our clients.

BIP is currently expanding its footprint in the United States, focusing on growing its Capital Markets and Financial Services lines. Our teams operate at the intersection of business strategy, technology, and data to help our clients drive smarter decisions, reduce risks, and stay ahead in a fast-evolving market environment.

Role Overview:

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.

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.

This role requires a hands-on Java engineer who can build high-throughput backend applications and data pipelines, optimize distributed processing workloads, and solve complex performance and data-quality challenges across batch and, where applicable, streaming environments.

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.

Key Responsibilities:

• 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…