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How much do bloomberg finance jobs pay per year?

As of Jun 24, 2026, the average yearly pay for bloomberg finance in the United States is $169,537.00, according to ZipRecruiter salary data. Most workers in this role earn between $136,500.00 and $198,500.00 per year, depending on experience, location, and employer.

What is the difference between Bloomberg Finance vs Bloomberg Financial Analyst?

AspectBloomberg FinanceBloomberg Financial Analyst
Required CredentialsTypically a bachelor's degree in finance, economics, or related fields; certifications like CFA are commonSame as Bloomberg Finance, often with additional certifications like CFA or CPA
Work EnvironmentCorporate offices, financial institutions, or remote; fast-paced, data-drivenOffice setting, focused on data analysis, reporting, and client interaction
Employer & Industry UsageFinancial services, investment firms, banks, and corporationsFinancial services, investment analysis, asset management firms

Bloomberg Finance generally refers to the broader financial services offered by Bloomberg, including data, analytics, and trading platforms. Bloomberg Financial Analyst is a specific role focused on analyzing financial data, preparing reports, and supporting investment decisions. While both roles require similar credentials and work in related environments, the analyst role is more specialized in data analysis and reporting within the Bloomberg ecosystem.

How does a Bloomberg Finance professional typically collaborate with other departments within the organization?

Bloomberg Finance professionals often work closely with teams such as sales, technology, product development, and client support to ensure the seamless delivery of financial solutions. Collaboration is key, as finance professionals may be involved in budgeting for new products, analyzing data to support business decisions, or communicating financial results to stakeholders. This cross-functional teamwork helps drive strategic initiatives and fosters a dynamic work environment, providing opportunities to learn from colleagues in diverse roles.

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

To excel as a Bloomberg Finance professional, you need a solid background in finance, analytics, and data interpretation, often supported by a degree in finance, economics, or a related field. Familiarity with Bloomberg Terminal, financial modeling tools, and relevant industry certifications such as CFA or FRM is typically required. Exceptional analytical thinking, attention to detail, and strong communication skills help professionals stand out in this fast-paced environment. These competencies are crucial for making informed financial decisions, delivering accurate insights, and supporting clients or stakeholders effectively.

What is Bloomberg Finance?

Bloomberg Finance refers to the financial products and services provided by Bloomberg L.P., a global financial technology and media company. Bloomberg is best known for its Bloomberg Terminal, a software system that provides real-time financial data, news, analytics, and trading tools to finance professionals. The company serves investment banks, asset managers, hedge funds, and other financial institutions with data, analytics, and market intelligence. Bloomberg Finance also includes media outlets, such as Bloomberg News and Bloomberg Television, which deliver financial news and analysis. Overall, Bloomberg plays a critical role in global financial markets by providing essential tools and information.
More about Bloomberg Finance jobs
What cities are hiring for Bloomberg Finance jobs? Cities with the most Bloomberg Finance job openings:
What states have the most Bloomberg Finance jobs? States with the most job openings for Bloomberg Finance jobs include:
What job categories do people searching Bloomberg Finance jobs look for? The top searched job categories for Bloomberg Finance jobs are:
Bloomberg Finance jobs near you
Infographic showing various Bloomberg Finance job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 14% Full Time, 57% Part Time, and 28% Contract. Highlights an 79% Physical, 10% Hybrid, and 11% Remote job distribution, with an average salary of $169,537 per year, or $81.5 per hour.
Senior Software Engineer - Distributed Data and Retrieval Platform

Senior Software Engineer - Distributed Data and Retrieval Platform

Bloomberg LP

New York, NY • On-site

$134K - $176K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 days ago

Job description

Senior Software Engineer - Distributed Data and Retrieval Platform
Location
New York
Business Area
Engineering and CTO
Ref #
10051421
Description & Requirements
Bloomberg runs on financial data. Every price, corporate action, benchmark, security master update, point-in-time view, and derived fact must be correct, fast, durable, and available at global scale.
Our team builds the distributed OLTP storage layer behind some of Bloomberg's most critical financial data systems. We provide deterministic, purpose-built APIs that let Bloomberg engineers read and write financial data safely, while our platform absorbs the complexity of Vitess, MySQL, MyRocks, RocksDB, sharding, replication, compaction, observability, capacity management, and failure recovery.
This is a role for engineers who want to work close to the metal of distributed data systems. You will reason about query routing, storage-engine behavior, schema evolution, read-your-own-write consistency, hot shards, p99 latency, saturation, compaction debt, replication lag, backfills, and safe production rollout.
When Vitess, MySQL, MyRocks, RocksDB, or related tooling need to change to meet Bloomberg's requirements, we are prepared to make those changes - and contribute them upstream.
Our Team
We build the store services that make Bloomberg financial data discoverable, queryable, point-in-time accurate, and reliable across the company.
Our systems expose structured, schema-evolving datasets through unified APIs while preserving consistency, low latency, operational safety, and auditability. They serve both latency-sensitive OLTP traffic and high-throughput readers that power downstream systems, including Bloomberg's S3-based BBDS lakehouse.
This role is not about Spark internals. It is about making a distributed OLTP storage platform remain correct and performant under very different workload shapes: small deterministic reads, write-heavy dataflows, backfills, table materialization, snapshot reads, and massively parallel batch access.
We care deeply about production behavior. That means source-level debugging, disciplined benchmarking, workload modeling, high-cardinality observability, automated operations, safe rollout, and tooling that helps engineers understand exactly why the system behaved the way it did.
What's in it for you
  • Build OLTP store services supporting billions of mutations and transactions across thousands of shards.
  • Work deeply with Vitess, MySQL, MyRocks, RocksDB, and the operational realities of running them at scale.
  • Design deterministic, low-latency access patterns instead of relying on arbitrary SQL execution.
  • Build systems for time series, bi-temporal data, point-in-time queries, versioned facts, snapshot reads, and derived table materialization.
  • Diagnose and improve performance across the stack: application code, JVM, Linux, networking, MySQL, MyRocks, RocksDB, and Vitess.
  • Build observability for fast production debugging using structured events, traces, high-cardinality dimensions, SLIs, and storage-engine telemetry.
  • Make store services robust under both client-facing OLTP traffic and highly parallel batch-reader workloads.
  • Influence the architecture of Bloomberg's financial data platform.
  • Contribute improvements back to upstream open-source systems when Bloomberg's requirements push beyond what exists today.
You'll need to have
  • 4+ years of professional software engineering experience.
  • Strong programming skills in one or more of Java, Go, C, or C++.
  • Deep experience or strong interest in database internals, distributed systems, storage engines, or large-scale data infrastructure.
  • Strong debugging skills across application code, infrastructure, networking, and Linux.
  • Experience reasoning from first principles about throughput, latency, contention, queuing, caching, compaction, replication, saturation, and failure modes.
  • A degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
We'd love to see
  • Contributions to infrastructure projects such as Vitess, MySQL, RocksDB, MyRocks, or similar systems.
  • Experience operating or extending sharded MySQL, Vitess, distributed SQL, or large-scale OLTP platforms.
  • Experience profiling and tuning production systems with JFR, async-profiler, perf, eBPF, flame graphs, heap analysis, or custom benchmarking frameworks.
  • A track record of building reliable systems where correctness, latency, and operability matter.
  • A passion for mentoring engineers and raising the technical bar of a platform team.

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.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.
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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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