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60 Bloomberg Data Engineer Jobs Hiring Near You

Bloomberg

Senior Software Engineer - BQL

Manhattan, NY · On-site

$135K - $178K/yr

Senior Software Engineer - BQL Location New York Business Area Engineering and CTO Ref # 10051731 ... The Bloomberg Query Language (BQL) is the nexus of this data access and distributed analytics.

Bloomberg

Senior Software Engineer - VAULT

Manhattan, NY

$135K - $178K/yr

... Bloomberg Big Data Management At the core of VAULT is big data at scale. Our systems handle massive ... Mentor junior engineers and contribute to an inclusive team culture You will need to have:

Bloomberg

Senior Software Engineer - BQuant

San Francisco, CA · On-site

$144K - $190K/yr

Senior Software Engineer - BQuant Location San Francisco Business Area Engineering and CTO Ref # 10050602 Description & Requirements BQuant is Bloomberg's cutting-edge financial research and data ...

Bloomberg LP

Senior Software Engineer - BQL

New York, NY · On-site

$134K - $176K/yr

Senior Software Engineer - BQL Location New York Business Area Engineering and CTO Ref # 10051731 ... The Bloomberg Query Language (BQL) is the nexus of this data access and distributed analytics.

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Bloomberg Jobs Information

What is it like to work at Bloomberg?

Bloomberg is known for its fast-paced and dynamic work environment, driven by a culture of innovation and collaboration that encourages employees to think creatively and push boundaries. The company's global teams work together to deliver real-time financial data and news, with a focus on providing accurate and unbiased information to its clients. For those who thrive in a challenging and rapidly evolving industry, Bloomberg offers opportunities to work on cutting-edge projects and develop skills in data analysis, journalism, and technology.
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Infographic showing various Data Engineer job openings at Bloomberg in the United States as of June 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 100% Physical job distribution.
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 7 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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