Bloomberg is the global leader in financial data and analytics. The Fixed Income and Derivatives Data Technologies Engineering department produces data, applications, and tools that enable our clients to generate trade ideas, structure deals, connect to electronic trading platforms, capture market movements, and assess and hedge portfolio risk for a variety of financial instruments across fixed income and derivatives asset classes. While building innovative technology is at the core of what we do, our department also develops sophisticated solutions for ever-evolving financial markets. We work directly with product managers, data management professionals, financial engineers, data engineers, and quantitative analysts to understand client and market needs. We use cutting edge big data technologies, distributed computing, functional programming, and machine learning to build software solutions that help us implement complex financial and quantitative models to facilitate pricing and analytics in real-time. What's in it for you? The Fixed Income and Derivatives Data Technologies Engineering group designs and builds high performance, low latency, distributed, and scalable data processing pipelines to extract, transform, and publish high quality financial reference data from external sources and into Bloomberg's ecosystem. We focus on building automated data processing pipelines using cutting-edge AI solutions and we complement that with manual remediation workflow tools. As a member of our group, you'll gain hands-on experience in designing and developing these systems, all while gaining an advanced knowledge of financial instruments and markets. We seek passionate and skilled engineers who thrive in a diverse, collaborative environment and excel at crafting reusable, efficient end-to-end solutions to complex problems. Proficiency in object-oriented programming languages like Python or C++ is greatly desired, with a willingness to learn new technologies. You will also have the opportunity to leverage open-source tools like Apache Kafka, MySQL, Solr, Spark, Kubernetes, Cassandra, and Redis (plus many more!) to design, develop, and implement full-stack solutions, adhering to industry best practices for software development, testing, automation, and CI/CD.