The Analytics Platform department builds the distributed infrastructure that powers Bloomberg's analytics ecosystem. Our systems process more than 700 billion requests every day, providing the foundation that enables Bloomberg applications, the Terminal, Enterprise products, and analytics services to access structured data and real-time content reliably at global scale.
As part of the team, you'll help modernize one of Bloomberg's most critical platforms by evolving a decades-old monolithic architecture into a cloud-ready, service-oriented ecosystem. You'll work on large-scale distributed systems spanning high-performance gateways, workload management, query execution, developer platforms, APIs, authorization, and core backend services. The focus is on solving challenging problems in scalability, low latency, reliability, resource management, and operational excellence while building reusable platforms that enable engineering teams across Bloomberg.
We're looking for engineers who enjoy designing robust distributed systems, optimizing performance at massive scale, and building infrastructure that other engineers depend on. If you're excited by high-throughput systems, complex architectural challenges, and writing software with company-wide impact, you'll find opportunities to work across multiple layers of Bloomberg's analytics platform and help shape its next generation.
Tech Stack
Programming Languages: Modern C++, Python
Frameworks: Project Reactor, Apache Kafka, Apache Arrow
Caching: Redis
Databases: Elastic Search, PostgreSQL, DuckDB, Cassandra, Comdb2, Parquet, Solr
Containerization: Docker, Kubernetes
CI/CD: Jenkins, SonarQube
Infrastructure: Linux, Microservices, Async frameworks
We'll trust you to
Shape the architecture of next-generation systems and design scalable, resilient microservices and APIs from the ground up.
Solve distributed systems challenges at multi-billion-request-per-day scale, optimizing latency, throughput, and resource efficiency.
Collaborate with dozens of Engineering teams—including data providers and client applications—to redefine how data flows across Bloomberg.
Build tooling, frameworks, and AI-driven automation that improve developer productivity and simplify operating large-scale distributed systems.
Deliver reliable, observable, production-quality software through rigorous testing and operational excellence.
Take ownership of projects end-to-end, define success, and drive execution.
Champion engineering best practices and mentor fellow engineers.
You'll need to have
4+ years of software engineering experience, ideally in Modern C++ or Python
Strong system design and distributed systems fundamentals.
Deep understanding of object-oriented design, data structures, and algorithms.
Experience building production-grade data infrastructure or distributed services.
Excellent collaboration and communication skills.
A degree in Computer Science, Engineering, Mathematics, a related field, or equivalent practical experience.
We'd love to see
Experience with frameworks such as Apache Arrow, Project Reactor, or Apache Kafka.
Hands-on experience building reactive, asynchronous, or event-driven applications in a service-oriented architecture.
Experience profiling, benchmarking, and optimizing system performance, including compute/memory trade-offs and low-latency design.
Knowledge of Linux systems programming or performance engineering.
Experience with databases (Elasticsearch, PostgreSQL) and caching systems (Redis).
Experience with cloud-native technologies such as Docker and Kubernetes.
Hands-on experience applying AI/ML techniques to engineering challenges and an interest in incorporating emerging technologies into production systems.
