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Senior Software Engineer - Anomaly Detection…
- Bloomberg (New York, NY)
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Senior Software Engineer - Anomaly Detection Platform
Location
New York
Business Area
Engineering and CTO
Ref #
10044221
Description & Requirements
Our team:
Bloomberg’s financial data and analytics are defined by their timeliness and quality. Our Anomaly Detection team is building a scalable, adaptable platform to help detect performance and data quality issues early in the development cycle across Bloomberg’s core data and analytics systems.
We thrive on collaboration and value diverse ideas. If you’re passionate about solving high-scale, high-availability challenges that drive meaningful impact, we’d love to talk to you.
The role:
We are seeking a highly skilled senior engineer to help evolve our platform into a more robust, scalable, and self-service solution. You will play a key role in designing and building infrastructure that powers various testing and anomaly detection capabilities, with a strong focus on reliability, extensibility, user experience for end users, and developer experience for teams extending the platform.
What’s in it for you:
You’ll tackle challenging problems at the intersection of platform engineering and large-scale data processing, helping to build a resilient system that identifies data anomalies and performance regressions in real time. You’ll collaborate with product owners, application developers, and infrastructure teams to deliver a seamless platform experience that enables faster testing and validation.
Your work will have a direct impact on the quality and stability of Bloomberg’s core financial data and analytics ecosystem. Beyond core engineering, you also have the opportunity to shape our broader strategy for ensuring data quality and software stability across the ecosystem.
You'll need to have:
+ 4+ years of professional software development experience in Python or similar languages
+ A degree in Computer Science, Engineering, Mathematics, a similar field of study or equivalent work experience
+ Hands-on experience designing and building large-scale distributed systems
+ Strong system design and problem-solving skills
We'd love to see:
+ Experience building platforms that serve a large number of tenants
+ Familiarity with large-scale data processing frameworks (e.g., Spark, Flink, Kafka)
+ Passion for data quality, performance analysis, anomaly detection
+ Familiarity with testing infrastructure, CI/CD workflows, or developer productivity tooling
+ Experience with owning end-to-end delivery of complex engineering projects
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.
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 parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email [email protected]
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