The DataHub Engineering team is building a distributed platform to host, catalog, discover, and deliver financial datasets across Bloomberg. This platform powers batch analytics, real-time stream processing, and low-latency, high-availability data distribution—ensuring that high-quality data, the lifeblood of financial markets, is always accessible.

As part of this mission, the DataHub Stream Functions team provides the managed, serverless infrastructure for scalable stream processing, enabling engineers across the company to focus on logic, not infrastructure. You’ll help shape a platform that standardizes and simplifies data processing at scale, touching virtually every corner of the Bloomberg engineering ecosystem.

Our tech stack:

• Languages: Java, Python, Go, TypeScript

• Frameworks/Tools: React, Kubernetes, Kafka

• Cloud-Native Stack: Container orchestration, service mesh, distributed tracing

• Developer Tools: VS Code extension, debuggers, observability instrumentation
  
  

You’ll get to work on:

• Automatic vertical scaling for stream applications

• Backfilling and backtesting solutions

• Kubernetes operators for workload rebalancing

• Controlled Kubernetes shell access for debugging

• DevX tooling: linters, plugins, and automation pipelines

• Connects and integration solutions

• Agentic workflows for streaming pipelines
  
  

What You’ll Need:

• 4+ years of hands-on experience in Java, Python or Go

• Experience building reliable, high-performance distributed services

• Deep understanding of Kubernetes, Linux, networking, and debugging

• Knowledge of software instrumentation and observability best practices
  
  

We’d love to see:

• Familiarity with the JVM ecosystem and performance tuning

• Frontend experience with React and TypeScript

• Background in stream processing frameworks (Kafka, Flink, etc.)

• Strong ownership mindset and empathy for end-users