Senior Data Management Professional - Data Engineering - Private Funds

USD 110,000-190,000 per year

SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

Agile @ 4 Communication @ 6 Data Analysis Data Engineering Data Pipelines Distributed Systems @ 4 ETL Machine Learning @ 4 NoSQL @ 6 Project Management @ 4 Python @ 6 Statistics @ 4

Details

Bloomberg’s Data organization delivers data, news, and analytics through innovative technology. The Alternative Investment Funds data team consists of data specialists and technologists focused on private markets, from fund launch to liquidation and seed round to IPO.

The Data Engineer will develop and maintain data pipelines, automation processes, and human-in-the-loop workflows that support Bloomberg’s Private Funds and Hedge Funds Data Products. The role also involves operational and product-focused data analysis, ETL development, prototype application design, project leadership, and end-to-end delivery in collaboration with Engineering and Product teams.

Responsibilities

Build and enhance data pipelines and processes powering Bloomberg’s Private Funds and Hedge Funds Databases while ensuring data quality, consistency, and reliability.
Identify automation opportunities and implement scalable ETL solutions, including human-in-the-loop data workflows and custom tooling.
Streamline and standardize data-pipelining practices across the team and broader department.
Collaborate with Engineering, Product, and Sales teams to gather requirements and deliver data solutions aligned with business goals.
Own production data pipelines and services, ensuring stability, reliability, and continuous improvement.
Contribute to technical development best practices, cross-team collaboration, operational standards, and service reliability.
Lead projects and own end-to-end project delivery.
Conduct technical training and mentor others.

Requirements

BA/BS degree or higher in Computer Science, Statistics, a relevant data technology field, or equivalent professional experience.
4+ years of Python programming and scripting experience in a production environment.
4+ years of experience working with NoSQL databases.
Understanding and experience with large-scale distributed systems.
Strong problem-solving skills, particularly in modifying and improving processes and workflows.
Excellent written and verbal communication skills, including the ability to explain 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.

Preferred Qualifications

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.

Benefits

Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.