As a Team Leader, you'll help define the technical vision for the platform while leading a team of engineers to deliver highly scalable and reliable solutions. You'll partner with engineering leaders and stakeholders across Bloomberg to shape the future of data quality engineering and build systems that improve developer productivity across the company.
Tech Stack
- Programming Languages: Python, Java
- Data Processing: Apache Spark
- Messaging: Apache Kafka, Distributed Message Queue Technologies
- Databases: PostgreSQL
- Containerization: Docker, Kubernetes
- CI/CD: Jenkins, SonarQube
- Infrastructure: Linux, Distributed Systems, Microservices
- AI & Automation: Machine Learning, AI-assisted Development Tools
What's in it for you?
If you're excited about leading engineers while solving large-scale distributed systems challenges, you'll have a home here.
As Team Leader for Anomaly Detection, you'll shape the strategy and technical direction of a platform that helps engineering teams across Bloomberg deliver reliable, high-quality analytics. You'll work with senior engineering leaders to define the roadmap, mentor engineers, and build innovative solutions that improve software quality across Bloomberg.
You'll have the opportunity to
Lead the technical evolution of Bloomberg's anomaly detection platform.
Define architecture for highly scalable distributed systems processing massive volumes of financial data and telemetry.
Build self-service platforms that improve developer productivity across Bloomberg Engineering.
Drive adoption of AI and machine learning techniques to enhance anomaly detection and operational automation.
Influence engineering practices and quality standards across multiple organizations.
Mentor and grow a high-performing engineering team while remaining technically engaged.
Partner with senior engineering leadership on strategic, high-impact initiatives.
We'll trust you to
Lead a team of software engineers through the design, development, and delivery of scalable anomaly detection platforms.
Define the technical roadmap and architecture for systems that improve data quality and engineering productivity across Bloomberg.
Drive technical decisions balancing scalability, performance, reliability, and operational simplicity.
Foster a collaborative engineering culture focused on ownership, innovation, and continuous improvement.
Mentor engineers through technical guidance, code reviews, architecture discussions, and career development.
Partner with stakeholders across Analytics Platform and other engineering organizations to prioritize initiatives and deliver shared infrastructure.
Build strong operational practices through observability, automation, testing, and continuous delivery.
Champion AI-assisted engineering practices and evaluate opportunities to apply machine learning to anomaly detection and intelligent automation.
Take ownership of strategic initiatives from conception through production while ensuring successful execution across multiple teams.
You'll need to have
Significant experience designing and building large-scale distributed systems and data-intensive applications.
Strong software engineering experience with Python, Java, or similar programming languages.
Demonstrated experience leading engineering teams or serving as a technical lead on complex, cross-functional projects.
Deep understanding of distributed systems, software architecture, and scalable platform design.
Experience building highly reliable, observable, and maintainable production systems.
Strong communication and stakeholder management skills with the ability to influence across organizations.
Experience mentoring engineers and fostering technical excellence.
A degree in Computer Science, Engineering, Mathematics, a related field, or equivalent practical experience.
We'd love to see
Experience leading platform or infrastructure engineering teams.
Experience with Apache Spark, Kafka, or other distributed data processing technologies.
Experience building developer platforms, internal tooling, or self-service infrastructure.
Knowledge of distributed messaging systems, event-driven architectures, and large-scale data pipelines.
Experience with Docker, Kubernetes, and cloud-native technologies.
Experience driving operational excellence through observability, automation, and reliability engineering.
Hands-on experience applying AI/ML techniques to engineering challenges, including anomaly detection, predictive analytics, or intelligent automation.
Contributions to large-scale infrastructure or open-source projects.
Passion for building inclusive, collaborative teams and developing future technical leaders.
If this sounds like you
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are, but in the meantime, feel free to have a look at this:
Introducing our Pune Engineering teams
Bloomberg Engineering
Technology at Bloomberg
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