Bloomberg - New York, NY
posted about 2 months ago
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 innovative workflow efficiencies, and we 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 equity markets. Our products run on intelligence and industry-specific insights provided by our 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 improve 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. The Company Financials Data Quality team is looking for a Data Engineer with a passion for Data Science and a deep interest in connecting diverse multifaceted, industry-specific data sets to drive product insights at scale. In this role you will need to develop a strong technical and practical understanding of how data is ingested into and consumed from our data processing and delivery technology stack to drive important customer outcomes. You are encouraged to use this knowledge to drive the evolution of our data anomaly detection systems to reduce errors in client-facing data, in part by analyzing large volumes of data and ensuring that it is ready to use. In order to do this, you'll lead and influence partners with varying levels of technical and product expertise, across Product, Data & Technology.