Senior Data Management Professional - Data Engineering - 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
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
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.
Our Team
Private Credit is one of the fastest-growing areas of financial markets, and Bloomberg's data helps clients monitor private credit deal flow, evaluate portfolio risk, and identify market trends. Our 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.
We work 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 is a key role within our organization responsible for optimizing the value of our data for clients and improving our data operations. They act as technical leaders setting the strategy for data products, developing interconnected data models, designing data architectures, ensuring data quality using various techniques, including programming, statistical methods and design thinking, to extract valuable insights from data. They are expected to be problem solvers, effective communicators, and versatile at balancing technical expertise with a product-focused approach.
Responsibilities
- Design, build, and maintain scalable data pipelines that support 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 that provide visibility into data quality, system health, and operational performance.
- Build dashboards, tooling, and self-service capabilities that improve transparency, efficiency, and decision-making across data operations.
- Partner with Product, Engineering, and Data teams to evolve the infrastructure and platforms supporting products and workflows.
- Identify bottlenecks and opportunities for automation, delivering 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 that 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.
We'd Love to See
- Experience with Bloomberg’s products or other financial data providers’ products
- Keen interest in and familiarity with generative AI frameworks andAgentic AI workflows
- Strong understanding of Fixed Income, Private Markets and reference data
- Experience with semantic structures, data modeling, or databases
- DAMA CDMP, DCAM certification a plus
- Project or work experience using one or more programming language 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
Benefits
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that 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.
The Company does not provide benefits directly to contingent workers/contractors and interns.