Senior Data Management Professional - Company Financials Foundational Support

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

The Company Financials team provides our clients with fast and accurate market-moving data so they can stay on top of their game: broker estimates, financial filings, and any other dataset that is useful to understand financial performance in the markets. Our products run on intelligence and industry-specific insights provided by the industry teams. We combine financial modeling, industry expertise, data management, and technical skills to curate critical metrics and drive insights from our data.

We are dedicated to crafting a best-in-class financial analysis and modeling product while constantly looking to enhance and expand our existing offering through a deep understanding of the markets we operate in, the sectors we cover, and our clients current and future needs.

What’s the Role?

As a Data Management Professional within the Foundational Support team, you will support the creation of scalable, high quality data workflows that underpin the delivery of accurate, fit-for-purpose datasets. Your work ensures that our foundational data processes not only meet accuracy and timeliness expectations but also evolve to support innovation, automation, and new commercial opportunities aligned with Bloomberg’s strategic goals.

You will play a pivotal role in validating end-to-end workflow orchestration, enhancing incident response and prevention frameworks, and embedding knowledge management and governance practices to strengthen data quality, transparency, and scalability across the Company Financials ecosystem.

We’ll trust you to:

• Own validation and optimization of dataset workflows and tooling to drive scalability, data quality, and process efficiency
• Lead feasibility assessments and proof-of-concept initiatives to evaluate and implement new tooling, automation, and dataset enhancements
• Drive root cause and impact analyses through data profiling and analytical assessment to identify systemic risks, design preventive measures, and embed long-term resiliency into data workflows.
• Partner cross-functionally with Product, Data, and Engineering teams to ensure alignment with strategic objectives, measurable ROI, and quality of workflow tooling release.
• Establish and maintain governance frameworks to ensure critical operational and dataset knowledge is structured, discoverable, and embedded into workflows for sustainable knowledge management.
• Develop best practices and process documentation that enable consistency, auditability, and scalability across onboarding and workflow execution.

You’ll need to have:

• 4+ years of professional experience in data quality management, or data governance
• Strong coding proficiency in SQL and Python for data analysis and workflow optimization idea generation
• Familiarity with ETL processes, data pipelines, and workflow design
• Experience with data visualization tools (Tableau, QlikSense, Power BI, or similar) to communicate quality insights
• Strong problem-solving skills and ability to thrive in a fast-paced environment
• Strong project management skills and ability to prioritize and adapt to tasks accordingly with a customer focused mentality
• Powerful collaboration skills to work across departments and regions, excellent written and verbal communication skills
• Strong analytical skills, attention to detail, and a solutions-oriented mindset
• Comfort working in a dynamic, evolving environment, balancing long-term strategy with immediate operational needs

We would love to see:

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.