Senior Data Management Professional - Data Quality - Dividend Forecasting
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Python @ 4
SQL @ 4
R @ 4
ETL @ 4
Data Science @ 4
Communication @ 4
BI @ 6
Project Management @ 4
Reporting @ 6
Power BI @ 6
Profiling @ 4
Data Pipelines @ 4
- 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.
Team
The Dividend Forecasting Data team monitors and interprets major company developments to identify themes or trends affecting key market sectors. The team is responsible for providing value beyond reported data using their financial knowledge to forecast key data‑points about a company that clients can use to understand the potential direction and magnitude of a company’s dividend payout. The team uses their sector and regional domain expertise to generate insightful content for client consumption.
Role Overview
You will help build effective data management solutions and promote practices to define, measure, and manage data quality of our datasets. You will apply data management standard methodologies, design quality checks and metrics in ETL processes, and help deliver quality data that is fit for purpose. To build and maintain domain expertise, you will be actively involved in the projection process and gain a deep understanding of how it all works. As a Senior Data Management Professional, you will work with different teams solving problems and devising solutions for data quality challenges, navigating unknowns and ambiguity while driving decisions and solutions.
Responsibilities
- Transform how we manage the quality of our datasets by applying industry best practices to devise quality checks and quality metrics in the ETL processes that create, transform and store data, and measure data against standards defined by our clients' needs
- Identify and advocate for opportunities to improve data quality through process improvements or workflow infrastructure enhancements
- Provide guidance on implementing processes to measure, monitor and report on data quality to internal partners in Product or Sales
- Develop, refine, and deliver the strategy for how to achieve best‑in‑class data quality and champion organizational change around data quality as a domain of data management
- Ensure data is fit‑for‑purpose and ready‑to‑use by proactively reviewing depth, timeliness and accuracy of datasets against user expectations
- Perform data profiling and apply statistical methods to support data quality measurements
- Partner with Product, Technology and Data Management Lab to ensure consistent principles are leveraged, data quality tools are fit for purpose, and results are measurable
- Keep up with industry trends, standards, and innovation in the Data Quality domain
Requirements
- 4+ years of professional experience in data quality management and/or establishing data governance metrics within Finance or Technology industries
- 4+ years of experience in crafting and developing data quality metrics and reporting using tools such as QlikSense and Power BI
- Understanding of ETL processes and broader data workflow engineering concepts
- Up‑to‑date knowledge of events taking place in the financial markets
- Demonstrable experience in data profiling/analysis using tools such as Python, R, or SQL
- Ability to lead multiple projects with global scope in parallel, with superb communication and stakeholder management skills
Preferred
- DAMA CDMP or DCAM certifications
- Familiarity with Corporate Actions, Equity Analysis, Portfolio Management, Dividend Futures, or Listed Derivatives asset classes
- Project management experience developed in a matrixed partner environment and cross‑regional business
- Experience of using Data Science to solve problems practically
- Managing and maintaining data pipelines to ensure reliable, high‑quality data flow
Compensation & Benefits
Salary Range: 110000 - 190000 USD annually + 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.
Bloomberg offers a comprehensive benefits plan 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) with match, life insurance, and various wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.