Senior Data Management Professional - Data Engineering (Data AI)

Details

Bloomberg's Data AI team builds AI-enhanced products at scale by curating model training data and improving internal processes through AI. The team develops evaluation and annotation frameworks that connect natural language processing with human judgment to improve the quality, intelligence, and usability of data powering Bloomberg's products.

As a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling that support 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 for delivering 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 that 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 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 equivalent qualifications.
• 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 to 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 stakeholder relationship management, communication, and cross-team collaboration skills.

Preferred Qualifications

• 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/evaluation datasets for ML or NLP models.
• Deep domain expertise in financial markets and news, with an understanding of customer needs.

Benefits

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