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Bloomberg Intelligence Jobs in California (NOW HIRING)

Cooley

Competitive Intelligence Analyst

San Diego, CA

... Bloomberg Law etc. and mining internal data in CRMs, business intelligence and financial systems ... Intermediate Excel skills - PivotTables, vlookup, charting, etc. * An understanding of the legal ...

Cooley

Competitive Intelligence Analyst

Palo Alto, CA · On-site

... Bloomberg Law etc. and mining internal data in CRMs, business intelligence and financial systems ... Intermediate Excel skills - PivotTables, vlookup, charting, etc. * An understanding of the legal ...

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$39

$59

$85

How much do bloomberg intelligence jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for bloomberg intelligence in California is $59.28, according to ZipRecruiter salary data. Most workers in this role earn between $52.21 and $63.80 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Bloomberg Intelligence Analyst, and why are they important?

To thrive as a Bloomberg Intelligence Analyst, you need a solid background in financial analysis, industry research, and often a degree in finance, economics, or a related field. Proficiency with financial modeling tools, Bloomberg Terminal, Excel, and data visualization platforms is typically required, alongside certifications like CFA being advantageous. Analytical thinking, strong written and verbal communication, and the ability to distill complex data into actionable insights set top performers apart. These skills ensure accurate, timely, and impactful research that helps clients make informed investment decisions.

What is the difference between Bloomberg Intelligence vs Bloomberg Data Analyst?

AspectBloomberg IntelligenceBloomberg Data Analyst
CredentialsTypically requires finance, economics, or related degrees; certifications like CFA are commonRequires strong analytical skills, proficiency in data tools, and often a degree in finance, economics, or computer science
Work EnvironmentResearch-focused, analytical, often in a team setting within financial servicesData processing, analysis, and reporting in a fast-paced financial environment
Employer & Industry UsageUsed by financial analysts, investors, and corporate clients for research and insightsUsed by financial firms, investment banks, and asset managers for data management and analysis

Bloomberg Intelligence primarily provides in-depth research and analysis on industries, companies, and markets, while Bloomberg Data Analysts focus on managing and analyzing financial data to support decision-making. Both roles are integral to financial services but differ in their core functions and skill sets.

How does the Bloomberg Intelligence role typically collaborate with other departments within Bloomberg, and what impact does this have on daily responsibilities?

Professionals in Bloomberg Intelligence frequently collaborate with sales, product, and technology teams, as well as external clients. This cross-functional teamwork ensures that research insights are aligned with client needs and market trends, and often requires adapting complex information for varied audiences. Daily responsibilities may include preparing sector reports, communicating findings to internal stakeholders, and responding to real-time data requests. This collaborative environment fosters a dynamic workflow and helps analysts develop a broad skill set, positioning them well for future advancement within Bloomberg.

What is Bloomberg Intelligence?

Bloomberg Intelligence (BI) is a research platform within Bloomberg that provides in-depth analysis, data, and insights on industries, companies, and global markets. It supports investment professionals by offering timely, comprehensive research and analytics to help them make informed decisions. BI covers a wide range of sectors and asset classes, delivering actionable information through the Bloomberg Terminal. Its analysts are experts in their fields, combining data-driven research with industry knowledge.
What are popular job titles related to Bloomberg Intelligence jobs in California? For Bloomberg Intelligence jobs in California, the most frequently searched job titles are:
What job categories do people searching Bloomberg Intelligence jobs in California look for? The top searched job categories for Bloomberg Intelligence jobs in California are:
What cities in California are hiring for Bloomberg Intelligence jobs? Cities in California with the most Bloomberg Intelligence job openings:
Bloomberg Intelligence jobs near you
Infographic showing various Bloomberg Intelligence job openings in California as of July 2026, with employment types broken down into 7% As Needed, 85% Full Time, 6% Part Time, and 2% Contract. Highlights an 79% Physical, 10% Hybrid, and 11% Remote job distribution, with an average salary of $123,293 per year, or $59.3 per hour.
Senior Software Engineer - Custom Data

Senior Software Engineer - Custom Data

Bloomberg LP

San Francisco, CA • On-site

$144K - $190K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

12th of 245 rated software companies

Job description

Senior Software Engineer - Custom Data
Location
San Francisco
Business Area
Engineering and CTO
Ref #
10052721
Description & Requirements
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 = 160,000 - 240,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981

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