Senior Data Management Professional - Workflow Optimization - Private Credit
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.
AI @ 4
Agentic AI @ 3
Communication @ 6
Data Engineering @ 6
Data Modeling @ 4
Data Pipelines @ 4
Data Visualization @ 3
ETL @ 4
Experimentation @ 4
GenAI
Generative AI @ 3
Machine Learning
Observability
Python @ 6
R @ 4
SQL @ 6
Tableau @ 3
- 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.
Details
Overview
Bloomberg runs on data. In Data, the team is responsible for delivering data, news, and analytics through innovative technology—quickly and accurately. The team applies problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance systems, products, and processes.
Our Team
Private Credit is one of the fastest-growing areas of financial markets. Bloomberg's data helps clients monitor private credit deal flow, evaluate portfolio risk, and identify market trends.
The team builds and maintains Bloomberg's BDC Direct Lending dataset by extracting, validating, and publishing loan-level data from public filings used across the Terminal and Enterprise products.
The work sits at the intersection of finance, data, and technology, partnering closely with Engineering, Product, AI, and clients to transform complex workflows through automation, improve data quality, and build scalable solutions that deliver trusted private credit data.
The Role
A Senior Data Management Professional optimizes the value of data for clients and improves data operations.
The role includes acting as a technical leader to set the strategy for data products, developing interconnected data models, designing data architectures, and ensuring data quality using techniques including programming, statistical methods, and design thinking.
The role requires being a problem solver, effective communicator, and versatile in balancing technical expertise with a product-focused approach.
Responsibilities
- Design, build, and maintain scalable data pipelines supporting data collection, annotation, training, evaluation, analytics, and reporting workflows.
- Develop and operate systems for dataset management, storage, versioning, and lifecycle governance to ensure reliable and reproducible AI workflows.
- Implement monitoring, observability, and alerting capabilities for visibility into data quality, system health, and operational performance.
- Build dashboards, tooling, and self-service capabilities to improve transparency, efficiency, and decision-making across data operations.
- Partner with Product, Engineering, and Data teams to evolve infrastructure and platforms supporting products and workflows.
- Identify bottlenecks and opportunities for automation to deliver scalable solutions that improve reliability, consistency, and operational efficiency.
Requirements
- Bachelor’s degree in Finance, Business, Economics, Accounting, STEM, or degree-equivalent qualifications.
- 3+ years in data engineering (Python, SQL).
- Experience building ETL/data pipelines at scale and creating data collection frameworks for structured and unstructured data.
- Experience with data modeling and developing proactive data quality strategies to ensure data is fit for purpose.
- Experience working with ML/AI datasets or experimentation workflows.
- Excellent problem-solving and analytical thinking skills with strong attention to detail.
- Proven track record of stakeholder relationship management, communication, and cross-team collaboration.
What We’d Love to See
- Experience with Bloomberg’s products or other financial data providers’ products.
- Interest in and familiarity with generative AI frameworks and Agentic AI workflows.
- Strong understanding of Fixed Income, Private Markets, and reference data.
- Experience with semantic structures, data modeling, or databases.
- DAMA CDMP or DCAM certification (plus).
- Project or work experience using one or more programming languages such as Python, SQL, and R.
- Familiarity with data visualization techniques and tools such as Tableau, QlikSense, or PowerBI.
- Proven ability to develop novel data architectures and products through 0-1 initiatives.
Compensation and Benefits
Salary Range = 110,000 - 190,000 USD Annual + Benefits + Bonus.
The referenced salary range is based on the Company’s good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training, and skill level.
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) + match, life insurance, and various wellness programs among others.