Senior Data Management Professional - Data Engineering (Data AI)

Details

Bloomberg runs on data. Its products are fueled by powerful information, combining data and context to provide clients with a complete picture around the clock and around the world. The Data organization delivers data, news, and analytics through innovative technology while identifying workflow efficiencies and implementing technology solutions to enhance systems, products, and processes.

Data AI contributes to building Bloomberg’s AI-enhanced products at scale by curating model training data and improving how internal processes use AI. The team provides evaluation and annotation frameworks that connect natural language processing with human judgment to improve the quality, intelligence, and usability of the data that drives Bloomberg’s products.

As a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling that power scalable AI and data workflows. You will enable reliable data collection, annotation, training, and evaluation processes by developing systems that improve data quality, operational visibility, and workflow efficiency. Through automation, observability, and platform engineering, you will help create the foundations that allow teams to deliver data and AI products with confidence and at scale.

Responsibilities

• Design, build, and maintain scalable data pipelines supporting 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 to 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 AI-enabled 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.
• At least 3 years of experience in data engineering, including Python and SQL.
• Experience building ETL and 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.

Preferred Qualifications

• Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
• Experience with semantic structures or large-scale data modeling.
• Experience using data visualization tools such as Tableau, QlikSense, or Power BI.
• Experience developing or managing annotation programs and training or evaluation datasets for ML or NLP models.
• Deep domain expertise in financial markets and news, as well as an understanding of customers’ needs.

Benefits

Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental, vision, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.