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 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.

Required Qualifications:

• 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.

Compensation:

** Base salary range for this role is $150,000 - $200,000**

Benefits:

• Choice of medical, dental, and vision insurance.
• Voluntary benefits.
• Short- and long-term disability.
• HSA and FSAs.
• Matching 401k.
• Discretionary performance bonus.
• Employee referral bonus.
• Employee assistance program.
• 11 public holidays.
• 20 days PTO.
• 7 Sick Days.
• PTO buy and sell program.
• Volunteer days.
• Paid parental leave.
• Remote/hybrid work environment support.

Equal Employment Opportunity:

It is BIP US Consulting policy to provide equal employment opportunities to all individuals based on job-related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship, or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these grounds.

BIP US provides a reasonable range of compensation for our roles. Actual compensation is influenced by a wide array of factors including but not limited to skill set, education, level of experience, and knowledge.