Our team

The Custom Data team helps clients to bring their firm’s private datasets into the Bloomberg ecosystem. It lets them link proprietary data stores directly to the Terminal and across our Enterprise suite, so teams can collaborate on the same live data, tailor workflows end-to-end, and embed custom analytics at every stage of the investment cycle (from idea generation through execution and post-trade reporting).

For buy-side firms like mutual funds, hedge funds and pensions, Custom data transforms the Terminal from a solo research tool into a shared intelligence platform.

The Custom Data platform delivers a managed infrastructure encompassing the end-to-end lifecycle of proprietary institutional data.

Key Capabilities

• Metadata and Access Management: Offers tools to define metadata for proprietary data and manage access to govern data access.

• Ingest Pipelines: Provides both interactive and batch ingest pipelines to facilitate the transfer of data from the client environment into the Bloomberg ecosystem.

• Rich Key Structure: Enables clients to store data against a combination of one or more financial attributes.

• Auditing Capabilities: Ensures the transparency and 'paper trail' necessary for regulatory compliance and internal data integrity.

• APIs for Integration: provides standardized Read APIs that seamlessly embed data within Bloomberg's ecosystem, including the Terminal, execution platforms, and risk workflows.

• Data Extraction: Supplies Data and Audit feeds to facilitate the extraction of client-provided data outside the Bloomberg ecosystem.

System Scale and Performance:

• The system processes in excess of 250 million daily requests, comprising 150 million metadata requests and 100 million read queries.

• It serves approximately 65 billion data points across interactive, reporting, batch, and screening applications.

• The platform manages data for 11,000 firms, encompassing 365,000 unique fields.

• It maintains stringent latency requirements to support real-time Bloomberg Terminal workflows.

We’ll trust you to:

• Design and implement features in the product while adhering to strict latency requirements.

• Write maintainable and production-quality code.

• Contribute to system design and refactor Python and C++ services to follow clean, single-responsibility principles.

• Evaluate next-generation storage solutions.

• Modernize Custom data integration with standard Bloomberg APIs.

• Own observability from metrics to dashboards, defining clear SLIs and SLOs.

• Design tools to improve team oncall/operational experience.

• Partner with other enterprise teams in Bloomberg to evolve the future of Custom data at Bloomberg.

• Mentor junior engineers in the team on best engineering practices.

You'll need to have:

• 4+ years of experience in backend engineering, ideally with Python

• Strong system design and debugging skills in production environments

• Familiarity with distributed messaging or stream-processing frameworks (Kafka preferred)

• Familiarity with relational and noSQL datastores at Bloomberg (Cassandra preferred)

• A strong product mindset paired with genuine empathy for client needs

• A degree in Computer Science, Engineering, or equivalent work experience

We’d love to see:

• Familiarity with Python standards and tooling

• Background in distributed systems like Kafka, Redis, Cassandra, or HBase

• Experience with CI/CD pipelines, automated testing, or system observability

• Exposure to containerized environments using Docker or Kubernetes

Salary Range = 160000 - 240000 USD Annually + Benefits + Bonus