Jobs and Careers
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Senior Software Engineer - Futures & Options
BloombergUnited Statesfull_timeVerifiedPosted 28 Feb 2026
💰 $240,000/yr($160,000/yr – $240,000/yr)
About the role
Senior Software Engineer - Futures & Options
Location
Skillman
Business Area
Engineering and CTO
Ref #
10049368
The global derivatives market is valued at over USD 540 trillion, and Bloomberg’s Listed Derivatives team builds the systems that allow traders, analysts, quants, and risk managers to navigate this massive, rapidly evolving landscape. We empower clients to perform idea generation, real-time market surveillance, historical analysis, volatility monitoring, and much more. Our product coverage spans options, futures, strategies, and spreads as well as the growing number of variations of each across every major global exchange.
Our team We are developing new frameworks to holistically acquire all publicly available exchange data from Kafka streams, APIs, SFTP, and various other data channels in order to modernize how Bloomberg ingests, consolidates, and distributes derivatives reference data. As the domain is accelerating in growth, , our mission is to construct a unified producer store that downstream teams across Bloomberg can rely on for consistent, timely, high quality data. Bonus: We have recently begun contributing to the Short Interest domain, which presents a similar business challenge. While this effort is independent from our work in derivatives, we are applying many of the same technical methodologies to drive change.
Tech Stack
Our backend systems focus on ETL pipelines and low-latency publication of high-volume real-time data into centralized producer stores. You’ll work primarily in Python, across a broad technical ecosystem including: Kafka, Bloomberg’s MQ (BMQ) | BBDS, comdb, Trino | DTP, DFR, BAIT | Redis | Bloomberg 3-Tier services and distributed storage systems.
What’s in it for you
You’ll have the chance to design and implement scalable data platforms that power Bloomberg’s derivatives ecosystem. You’ll work on distributed systems and low-latency ETL pipelines that process high-volume market data, collaborating with engineers and product partners across the organization. This role offers deep technical challenges, visibility across multiple asset classes, and the opportunity to influence data engineering best practices firmwide.
We’ll trust you to
You’ll need to have
Description & Requirements
The Core Financial Analytics team provides the foundational pricing, analytics, and data infrastructure that powers Bloomberg’s markets business. The group delivers cross-asset solutions for curves, volatility surfaces, consensus pricing, screening tools, and listed derivatives, ensuring that clients and internal systems have access to accurate, transparent, and real-time market data.The global derivatives market is valued at over USD 540 trillion, and Bloomberg’s Listed Derivatives team builds the systems that allow traders, analysts, quants, and risk managers to navigate this massive, rapidly evolving landscape. We empower clients to perform idea generation, real-time market surveillance, historical analysis, volatility monitoring, and much more. Our product coverage spans options, futures, strategies, and spreads as well as the growing number of variations of each across every major global exchange.
Our team We are developing new frameworks to holistically acquire all publicly available exchange data from Kafka streams, APIs, SFTP, and various other data channels in order to modernize how Bloomberg ingests, consolidates, and distributes derivatives reference data. As the domain is accelerating in growth, , our mission is to construct a unified producer store that downstream teams across Bloomberg can rely on for consistent, timely, high quality data. Bonus: We have recently begun contributing to the Short Interest domain, which presents a similar business challenge. While this effort is independent from our work in derivatives, we are applying many of the same technical methodologies to drive change.
Tech Stack
Our backend systems focus on ETL pipelines and low-latency publication of high-volume real-time data into centralized producer stores. You’ll work primarily in Python, across a broad technical ecosystem including: Kafka, Bloomberg’s MQ (BMQ) | BBDS, comdb, Trino | DTP, DFR, BAIT | Redis | Bloomberg 3-Tier services and distributed storage systems.
What’s in it for you
You’ll have the chance to design and implement scalable data platforms that power Bloomberg’s derivatives ecosystem. You’ll work on distributed systems and low-latency ETL pipelines that process high-volume market data, collaborating with engineers and product partners across the organization. This role offers deep technical challenges, visibility across multiple asset classes, and the opportunity to influence data engineering best practices firmwide.
We’ll trust you to
- Build and optimize back-end data pipelines for high-volume, low-latency publishing into centralized producer stores.
- Design, implement, and deploy ETL workflows and platforms that support modern data acquisition and distribution.
- Collaborate with partner teams and stakeholders to align data models and ensure reliability and scalability.
- Improve data quality, timeliness, and consistency through automated validation and monitoring.
- Contribute to architectural discussions and mentor other engineers on best practices in distributed systems and data engineering.
You’ll need to have
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