Senior Software Engineer — Distributed Data and Retrieval Platform

Details

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.

Responsibilities

• Build and operate distributed OLTP store services that support billions of mutations and transactions across thousands of shards.
• Design deterministic, low-latency access patterns and APIs for structured, schema-evolving datasets.
• Work on systems that serve both latency-sensitive OLTP traffic and high-throughput readers (including integration with Bloomberg’s BBDS lakehouse).
• Diagnose and improve performance across the stack: application code, JVM, Linux, networking, MySQL, MyRocks, RocksDB, and Vitess.
• Implement and improve observability for fast production debugging using structured events, traces, high-cardinality dimensions, SLIs, and storage-engine telemetry.
• Perform source-level debugging, disciplined benchmarking, workload modeling, and build tooling for automated operations and safe rollouts.

Requirements

• 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.

Nice to have / Additional Expertise

• 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.
• Track record of building reliable systems where correctness, latency, and operability matter.
• Passion for mentoring engineers and raising the technical bar of a platform team.

Compensation & Benefits

• Salary Range: 160,000 - 240,000 USD Annual + Benefits + Bonus.
• The posting states a comprehensive benefits plan 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) with match, life insurance, and various wellness programs. The company does not provide benefits directly to contingent workers/contractors and interns.

Team & Focus

• The team focuses on making distributed OLTP storage correct, low-latency, and operationally safe across diverse workload shapes including small deterministic reads, write-heavy dataflows, backfills, table materialization, snapshot reads, and massively parallel batch access.
• Emphasis on source-level debugging, high-cardinality observability, automated operations, and contributing upstream when Bloomberg’s needs exceed current open-source capabilities.