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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Reference Data Software Engineer - **Company:** Business Integration Partners USA Inc. - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $120,000.0 - $160,000.0 - **Contract:** Permanent contract - **Skills:** .NET Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, C Sharp (Programming Language), Common Lisp Object Systems, Code Review, Databases, Relational Databases, Database Development, Programming Tools, Entity Relationship Models, Graph Database, Python (Programming Language), Reference Data, Software Tools, Standard Sql, Scaled Agile Framework, Software Engineering, Systems Integration, Data Processing, Enterprise Software Applications, Large Language Models, Snowflake, Caching, Backend, Production Code, Data Management, Static Data, Api Design, Microservices - **Published:** September 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=07db2c33d9bd34fc ## About the Role · 5+ years of professional software engineering experience, with hands-on experience building enterprise applications, data platforms, or server-side systems. · Strong hands-on development experience with C#/.NET and Python. · Solid server-side/middle-tier engineering experience, including APIs, microservices, messaging, caching, and system integrations. · Experience developing data-processing components involving ingestion, transformation, cleansing, validation, or enrichment. · Strong SQL and database development skills. · Experience with relational databases; exposure to graph, object, or other database technologies is beneficial. · Experience implementing data models and working with complex data relationships. · Experience working with Reference Data, Security Master, Master Data Management, securities data, or comparable enterprise data domains. · Understanding of securities and investment data, ideally including exposure to credit instruments such as loans, bonds, or CLOs. · Experience within asset management, investment management, capital markets, banking, or financial services. · Experience working in cloud-based engineering environments; Azure experience is particularly relevant. · Practical experience using AI-assisted engineering tools, coding assistants, or LLM-based development technologies. · Strong analytical and problem-solving skills with the ability to understand requirements and execute against defined technical designs. · Strong communication skills and ability to collaborate effectively with engineers, analysts, PMs, and business stakeholders. Preferred Qualifications · Experience with Security Master or Reference Data platforms. · Familiarity with security identifiers such as CUSIP, ISIN, SEDOL, and FIGI. · Experience with identifier mapping, cross-reference processing, golden records, or entity resolution. · Exposure to corporate actions and their impact on security/reference data. · Experience with private credit, private equity, alternative assets, or broader private-markets data. · Hands-on experience with Azure and/or Snowflake. · Experience with graph databases or complex issuer/security/legal-entity relationship models. · Experience with messaging-driven or event-driven applications. · Experience applying AI tools to software development, data quality, entity matching, or engineering productivity., * Do you have 5+ years of professional software engineering experience, including hands-on development of enterprise server-side or middle-tier applications? * Do you have hands-on development experience with C#/.NET and Python, including APIs, microservices, messaging, or data-processing components? * Do you have experience working with Reference Data, Security Master, securities/investment data, or another complex master-data domain? Education: * Bachelor's (Required) ## Description We are seeking a hands-on Reference Data Software Engineer with 5+ years of professional software engineering experience to develop and enhance enterprise reference data platforms supporting investment-management and front-office workflows. This role is focused on software development, engineering execution, and delivering production-quality features and functionality within an established technical architecture. The successful candidate will work across security master and organization static data platforms supporting public and private equity, credit, derivative, and other financial instruments. The ideal candidate brings strong hands-on C#/.NET and Python development experience, solid server-side engineering capabilities, and experience working with APIs, microservices, messaging, caching, databases, and data-processing components. Experience with securities, reference data, security master, or investment data is highly valuable. The focus is on being a strong engineer who can understand defined designs and requirements, solve technical problems, and execute effectively. Key Responsibilities · Develop and enhance enterprise Reference Data and Security Master applications supporting investment-management workflows. · Build production-quality server-side services and components using C#/.NET and Python. · Implement APIs, microservices, messaging-based integrations, caching solutions, and other middle-tier/backend functionality. · Develop and maintain data-processing workflows covering ingestion, transformation, cleansing, validation, enrichment, and distribution. · Implement reference data models supporting securities, issuers, organizations, legal entities, identifiers, and related relationships. · Work with relational and other database technologies to support reference data storage, retrieval, cross-referencing, and golden-record processes. · Translate functional and technical requirements into reliable, maintainable software solutions. · Collaborate with senior engineers, architects, business analysts, PMs, and business users to deliver new functionality. · Write clean, testable, production-quality code and participate in code reviews, testing, deployment, and troubleshooting. · Diagnose and resolve application, integration, and data-related issues within production environments. · Use modern AI-assisted development tools and LLM-based coding assistants to improve engineering productivity and accelerate delivery. · Contribute to globally distributed Agile engineering teams and deliver against established technical designs and development standards.