The DataHub Engineering team provides a distributed platform for hosting datasets, complete with managed data stores, search, discovery, lakehouse and real-time stream processing capabilities. The platform provides a single place in the company to discover, access, publish and subscribe to data.

　　This is the team that introduced the abstraction of "dataset", invented a schema language to formally define all data at Bloomberg, complete with schema evolution, versioning, and a true point in time semantics. We're the first to introduce Kafka, Avro, company-wide Dataset Schema Registry, Mesos, Clustered MySQL, Vitess and Spark for ETL, at Bloomberg for designing this new Data Intensive Platform that is the hub of financial datasets.

　　The DataHub's Data Pipe Infrastructure, built on Apache Kafka, streams the most critical datasets influencing the financial markets.

　　We'll trust you to:

　　Write software for Kafka based Data Pipes for the company wide Data Mesh Debug and diagnose intricate failures, functional and performance regressions, with Apache Kafka, data codecs, low latency services, Spark streaming Contribute to upstream bug reports and commits. Collaborate and share extensively with fellow engineers

　　You'll need to have:

　　4+ years experience programming in Java/Scala Expertise in Apache Kafka and Distributed Systems A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience Experience building reliable data infrastructure

　　Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

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