Bloomberg Portfolio Analytics empowers the most prominent players in the financial world to handle their portfolios, assess exposures, and make decisions that move the markets.

The Portfolio Data Integrity team is responsible for the infrastructure which automatically verifies the quality of the datasets utilized by flagship Enterprise products on the Bloomberg Terminal including Enterprise Portfolio Analytics and Bloomberg Barclays indices. We build the distributed infrastructure and automated systems employed by key stakeholders such as Bloomberg Index managers, global data specialists, risk analytics quants, and portfolio reliability engineers across the globe (NY, London and Singapore) to assure that the analytics published by these products are of the highest quality and correctness. These datasets are used by our clients not only to make critical investment decisions in managing portfolios worth billions of dollars, but are also used as reference for the trillion dollar FI/Bonds and derivatives markets. If you’re looking for an opportunity to leave your technical mark in a domain with truly global impact on the financial markets, this team and these challenges are for you!

Our tech stack is built out of state-of-the-art industry standard technologies and languages. The data quality assurance system is a data science platform with a back-end based on Python, Spark, Kubernetes, Cassandra, Redis and S3 based storage, and a front-end based on Qlik Sense, SOLR and the Bloomberg UI. Clients provide the business logic rules using Python.

We strive to continuously improve our systems and leverage new technologies. The team is actively investing in a virtual elastic platform based on Kubernetes, expanding the scope of our engine to new client facing applications, and our area of ownership is ripe for the application of machine learning techniques to perform anomaly detection and decision execution. We evaluate our solutions through system analysis and back-testing given the critical nature of the reliability and scalability of our systems.

We embrace automatic testing under Jenkins, and use monitoring technologies such as Splunk, Humio, GUTS, Grafana and Jupyter notebooks. Our team follows Agile-methodology, and are pushing forward to a fully continuous integration and release process.

As a member of the team, we’ll trust you to:

• Design and deploy solutions to tackle financial-industry challenges, taking ownership of the full development cycle, including close collaboration with product and engineering partners
• Perfect and grow our software infrastructure, exploring and evaluating new technologies both within and outside of Bloomberg to tackle our next scalability challenge
• Embrace working together as a team – mentoring and learning from existing teammates, constructively proposing improvements to projects owned by others, and being all hands on deck in case of emergencies

You'll need to have:

• 3+ years of programming experience in C++, Java or Python
• In depth analytical skills and solid understanding of data structures and algorithms
• Experience in the full software development cycle and a thorough understanding of the systems you worked on
• Strong verbal and written communication skills
• BA, BS, MS, PhD in Computer Science, Electrical Engineering or related technology field

We'd love to see:

• Familiarity with technologies like Apache Spark, Arrow, Solr and experience with machine learning
• Interest in data quality automation, ETL and ELT systems.
• A passion for continually improving/optimizing software and procedures.

Bloomberg is an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.