Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Java @ 7
Mathematics @ 4
PostgreSQL
Python
Software Development @ 6
Statistics @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
The BQL and Semantic Platform group builds core query and semantic infrastructure used to access, analyze, model, and organize Bloomberg data. The team develops Bloomberg Query Language (BQL), a semantic platform for defining and managing semantic artifacts, and Bloomberg's RDF triplestore infrastructure.
The role focuses on developing the database itself, including graph storage and query-processing internals, rather than solely deploying or operating an existing database product. The platform stores semantic models and large RDF datasets and is designed to make billions of RDF statements efficiently queryable with enterprise-grade performance, correctness, availability, and reliability.
Responsibilities
- Develop and operate RDF triplestore infrastructure.
- Work on physical storage and indexing, SPARQL query planning and execution, transaction and isolation semantics, statistics and cardinality estimation, inference, replication, scalability, and operational reliability.
- Build database and graph database internals supporting large-scale RDF datasets.
- Diagnose and optimize database performance, including memory, I/O, query planning, and storage bottlenecks.
Technologies
RDF4J, LMDB, RocksDB, PostgreSQL, Java, Python, SPARQL, SHACL, RDF, and inferencing.
Requirements
- 4+ years of professional software development experience.
- A degree in Computer Science, Engineering, Mathematics, a related field, or equivalent practical experience.
- Hands-on experience developing database or graph database internals, rather than solely building applications on top of databases.
- Experience developing RDF triplestore, labeled property graph, or closely related graph database infrastructure.
- Strong understanding of several database implementation areas, including storage engines, indexing, physical data representation, query planning and execution, transactions, concurrency, isolation, cardinality estimation, database statistics, caching, memory management, disk I/O, replication, recovery, and high-availability architecture.
- Strong software engineering skills in Java or another systems-oriented programming language.
Preferred Qualifications
- Deep experience with Eclipse RDF4J, Apache Jena, or another RDF triplestore implementation.
- Experience with labeled property graph database internals or graph query engines.
- Experience implementing or optimizing SPARQL, Cypher, Gremlin, or other graph query languages.
- Experience with RDF or graph storage layouts and indexing strategies.
- Experience contributing to or modifying open-source database engines.
- Experience with LMDB, RocksDB, or other embedded key-value or storage engines.
- Knowledge of RDF, SPARQL, SHACL, inference, and Semantic Web standards.
- Experience diagnosing database performance at large scale, including memory, I/O, query planning, and storage bottlenecks.
Benefits
Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs. The position offers a salary range of $160,000–$240,000 USD annually, plus benefits and bonus. Actual compensation may vary based on geographic location, work experience, market conditions, education or training, and skill level.