Bloomberg runs on data, and as part of the Data team, we're responsible for acquiring it, providing it to our clients and helping derive significant insights out of it. We collect, analyze, process, and publish the data, which is the backbone of our iconic Bloomberg Terminal and our enterprise products - the facts and figures which ultimately move the financial markets. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to improve our systems, products, and processes.

Our Team:

Whether a fund investor, manager or advisor, Bloomberg has the data, solutions and industry network to help our clients take their fund and company analysis to the next level. The Alternative Investments data team is made up of data specialists and technologists with a passion for private markets, from fund launch to liquidation, seed round to IPO and all the data in between.

What’s the role?

The Alternative Investment Funds Data Engineer team is a dynamic group of individuals who tackle the more challenging aspects of our data product including data pipelining and sophisticated data analysis. Our Data Engineers possess a unique combination of technical skills and an interested in business, as well as good communication and interpersonal skills. As such, we are looking for a highly motivated individual with a passion for data and the technology that surrounds it.

As a Data Engineer you will apply your problem-solving skills to handle the data pipelines, automation processes and human-in-the-loop workflows that feed our Alternative Investment Funds Data Products. In addition to the data pipelining work, you will analyze our data from an operational as well as product standpoint. This might be by building the associated ETLs or by designing prototype applications with our product teams. You will be expected to lead projects, collaborate with Engineering and Product, and mentor junior members of the group who are looking to develop technically.

We’ll trust you to:

• Develop and support the data pipelines and processes that feed our Bloomberg Hedge Fund and Private Funds Databases
• Find opportunities and build automated solutions for ETL pipelines, human-in-the-loop data processing, and tooling to scale the growth of our product
• Draw on technical knowledge to scale and standardize pipelining across the team and the department
• Partner with a wide variety of team members including Engineering, Product and Sales on product development and execution
• Take ownership and ensure continuity of current data pipelines and services in production
• Contribute to improving the team’s operational standard methodologies around end-to-end technical development, team member collaboration and ensuring reliability of current services in production

You’ll need to have:

• A BA/BS degree or higher in Computer Science, Mathematics, or relevant data technology field, or equivalent professional work experience
• 3+ years of Python programming and scripting in a production environment
• 3+ years of experience working with NoSQL databases
• Understanding and experience of large-scale distributed systems
• Strong problem solving skills, particularly to modify and improve processes and workflows
• Excellent written and verbal communication skills, especially when explaining technical processes and solutions to business partners and management
• High attention to detail and degree of shown decision-making and problem-solving skills
• Ability to work independently as well as in a distributed team environment
• Ability to influence others and lead change
• Experience in conducting technical training and mentoring others

We’d love to see:

• Financial Markets experience including an understanding of the private equity industry
• Understanding of Machine Learning, applied statistics and data analytics
• Agile/Scrum Project Management experience

Does this sound 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.