Senior Data Management Professional - Data Engineering - Private Funds

Details

Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.

Team overview

The Alternative Investment Funds data team consists of data specialists and technologists focused on private markets, from fund launch to liquidation, seed round to IPO and all the data in between. The team supports Private Funds and Hedge Funds data products.

Role summary

As a Data Engineer you will handle data pipelines, automation processes and human-in-the-loop workflows that feed Bloomberg's Private Funds and Hedge Funds Data Products. You will analyze data from both operational and product standpoints, build ETLs, design prototype applications with product teams, lead projects, collaborate with Engineering and Product, and own end-to-end delivery of projects and production services.

Responsibilities

• Build and enhance data pipelines and processes that power Bloomberg’s Private Funds and Hedge Funds databases, ensuring high data quality, consistency, and reliability.
• Identify opportunities for automation and implement scalable ETL solutions, including human-in-the-loop data workflows and custom tooling.
• Streamline and standardize pipelining practices across the team and broader department to promote efficiency and knowledge sharing.
• Work closely with Engineering, Product, and Sales teams to gather requirements and deliver end-to-end data solutions that align with business goals.
• Take full ownership of existing data pipelines and services in production, ensuring their stability, reliability, and continuous improvement.
• Contribute to operational standards and best practices in technical development, cross-team collaboration, and service reliability.

Requirements

• BA/BS degree or higher in Computer Science, Statistics, or relevant data technology field, or equivalent professional work experience.
• 4+ years of Python programming and scripting in a production environment.
• 4+ years of experience working with NoSQL databases.
• Understanding and experience in large-scale distributed systems.
• Strong problem-solving skills with the ability to modify and improve processes and workflows.
• Excellent written and verbal communication skills for explaining technical processes and solutions to business partners and management.
• High attention to detail and demonstrated decision-making and problem-solving abilities.
• Ability to work independently and in a distributed team environment.
• Ability to influence others and lead change; experience conducting technical training and mentoring others.

Preferred / Nice-to-have

• Financial markets experience, including an understanding of the private markets industry.
• Understanding of Machine Learning, applied statistics, and data analytics.
• Agile/Scrum project management experience.

Compensation & Benefits

• Salary range: 110,000 - 190,000 USD annual + benefits + bonus.
• Benefits 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) with match, life insurance, and various wellness programs. (Company does not provide benefits directly to contingent workers/contractors and interns.)