Senior Data Management Professional - Company Financials Foundational Support

Bloomberg•Princeton, FL

About The Position

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. 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. 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.

Requirements

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

Nice To Haves

Industry-recognized data management certifications (e.g., DAMA, CDMP, DCAM)
Experience with company financials data and financial statements
Hands-on knowledge of data governance and quality frameworks, including metadata management and regulatory considerations
Knowledge of software testing and QA methodologies with experience in both manual and automating testing processes
Familiarity with modern data infrastructure and architecture (APIs, pipelines, cloud platforms), with exposure to AI/ML or LLM-based enrichment solutions for anomaly detection and automation
Experience using Bloomberg Terminal and Company Financials products
Exposure to Agile methodologies

Responsibilities

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.