Bloomberg is the global leader in business and financial data, news and insight. Using the power of technology, we connect the world's decision makers to accurate information on the financial markets - and help them make faster, smarter decisions.
We're now going one step further We are building a new product from scratch to open up our data, core products and visualizations to data scientists, ML researchers, and quantitative modelers. Our users can now fetch and interact with Bloomberg data and products using Python, and apply all the tools of the data science ecosystem to their analyses, unlocking unprecedented flexibility and customizability.
Where do you come in? You can help our users focus on gaining insights from data, by seeking to understand and address their friction points in accessing and analyzing data. How do they discover datasets relevant to their research? How do they easily understand characteristics of a dataset? How do they easily combine data across multiple sources and formats?
Join us in understanding and solving the questions above, as well as other friction points that distract users from their core analysis.
When our users are able to easily discover and retrieve data programmatically from a vast number of Bloomberg datasets, and seamlessly combine these with their own datasets, they will have powerful, new ways to make sense of financial and business data to guide their investments.
Who are you?
You are an experienced full-stack engineer with an interest in building data discovery and data blending tools
You can take large, ambiguous problems and turn them into concrete execution plans through research, scoping, and close collaboration with stakeholders
Collaborating with your team, you take time to analyze different solutions and communicate tradeoffs well
You have experience mentoring junior engineers
We'll trust you to:
Build APIs and features to help users easily browse, discover and access Bloomberg datasets relevant to the companies and financial instruments they are researching
Build tools to allow users to work seamlessly with data from disparate sources
Stay up to date with industry developments in data querying and data storage formats, such as Presto, Apache Iceberg, and more
Develop and deploy robust software requiring minimal maintenance
You need to have:
5+ years of production experience in Python, Java, C++ or other programming languages
Experience supporting production systems
An understanding that software should be kept as simple as possible
BA, BS, MS, or PhD in Computer Science, Engineering or related technology field, or equivalent experience
We'd love to see:
Experience with open source or native cloud solutions for managing interactive data querying across disparate data sources and formats, such as Presto or Amazon Athena (based on Presto)
Experience building full-stack applications, including service APIs and database design
An appreciation for how our data sets underpin the world's financial systems - if you don't know anything about finance, you'll pick it up by interacting with a world-class team of market experts.
If this sounds like you, apply! Bloomberg has funded major initiatives in the Project Jupyter community, such as JupyterLab, Voilà (a Jupyter dashboarding solution), and a JupyterLab debugger. Your teammates will be ACM Software System Award-winning Project Jupyter members! See them discussing their work at:
We recently posted a "meet the team" blog post, check out the link below to get to know our SF engineering office! https://www.techatbloomberg.com/blog/meet-the-teams-sf-engineering/
Bloomberg is an equal opportunities employer, and we 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.