Location

Skillman

Business Area

Engineering and CTO

Ref

10049368

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

- 4+ years of experience in software engineering with proficiency in Python.
- Experience building or maintaining distributed data systems or ETL pipelines.
- Working knowledge of streaming and messaging technologies such as Kafka or BMQ.
- Familiarity with relational or distributed query systems (e.g., Trino, Redis, DTP).
- A degree in Computer Science, Engineering, Mathematics, similar field of study, or equivalent work experience.

We’d love to see

- Experience with large-scale data processing, low-latency systems, or real-time analytics.
- Familiarity with Bloomberg’s internal infrastructure (3-Tier, BBDS) or similar frameworks.
- Knowledge or interest of financial markets, especially derivatives or reference data.
- A collaborative mindset with an interest in mentoring and growing technical depth across the team.
- Strong motivation to partner across teams to achieve cohesive, department-wide success on domain-specific problems.

Salary Range

160000 - 240000 USD Annually + 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.

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