Senior Data Management Professional - Data Engineering (Data AI)
About The Position
Bloomberg’s Data organization delivers data, news, and analytics through technology, with a focus on improving workflows and implementing technology solutions. Data AI helps build Bloomberg’s AI-enhanced products by curating model-training data and improving how internal processes use AI. The team develops evaluation and annotation frameworks that connect natural language processing with human judgment to improve the quality and usability of data. As a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling for scalable AI and data workflows. You will enable reliable data collection, annotation, training, and evaluation by developing systems that improve data quality, operational visibility, and workflow efficiency. Through automation, observability, and platform engineering, you will help establish foundations for teams to deliver data and AI products reliably and at scale.
Requirements
- Bachelor’s degree in Finance, Business, Economics, Accounting, or STEM, or degree-equivalent qualifications.
- At least 3 years of data engineering experience, including Python and SQL.
- Experience building ETL/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 track record of stakeholder relationship management, communication, and cross-team collaboration.
Nice To Haves
- Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
- Experience in semantic structures or large-scale data modeling.
- Experience using data visualization tools such as Tableau, QlikSense, or PowerBI.
- Experience developing or managing annotation programs and training/evaluation datasets for ML or NLP models.
- Deep domain expertise in financial markets/news and understanding of customers’ needs.
Responsibilities
- Design, build, and maintain scalable data pipelines for data collection, annotation, training, evaluation, analytics, and reporting workflows.
- Develop and operate systems for dataset management, storage, versioning, and lifecycle governance to support reliable and reproducible AI workflows.
- Implement monitoring, observability, and alerting 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 infrastructure and platforms supporting AI-enabled products and workflows.
- Identify bottlenecks and automation opportunities, delivering scalable solutions that improve reliability, consistency, and operational efficiency.
Benefits
- Merit increases
- Incentive compensation for exempt roles
- Paid holidays
- Paid time off
- Medical benefits
- Dental benefits
- Vision benefits
- Short- and long-term disability benefits
- 401(k) with match
- Life insurance
- Wellness programs
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What This Job Offers
Job Type
Full-time
Career Level
Senior
