Senior Data Quality & Automation Lead

Bloomberg; Princeton (NJ); On-site; USD 110,000 - 190,000; Full time

Benefits offered by this job

Comprehensive benefits

Bonus program

401(k) match

Job summary

Bloomberg's People Data team in Princeton is seeking a Senior Data Management Professional who can transform how we acquire, onboard, maintain, and validate data through automation and AI-enabled workflows. You will design scalable data quality solutions, reduce manual effort, and collaborate with Data, Product, Enterprise, and Engineering to expand coverage and improve reliability.

This role offers a fast-paced, collaborative environment with opportunities to innovate across data, operations,

Qualifications

• BA/BS or equivalent work experience in a related field.
• 3+ years data quality/management experience in finance or tech.
• Experience applying AI/ML to data acquisition and workflows.
• Experience developing data quality metrics and rules.
• Strong Python and production-grade data workflow experience.

Responsibilities

• Design scalable data quality and automation solutions for People Data.
• Automate data acquisition and expand coverage across datasets.
• Identify bottlenecks and translate them into automation opportunities.
• Collaborate with Data, Product, Enterprise, and Engineering teams.
• Define success metrics for automation impact and data quality.
• Educate colleagues on data quality and scalable data management principles.
• Keep up with trends in data quality, AI, and engineering domains.
• Work in a fast-paced, collaborative setting.

Skills

Python

Data quality

Automation

Data pipelines

Communication

Project management

Education

BA/BS in CS, Math, Information Systems, Finance, or related field

Tools

Tableau

QlikSense

Job description

Bloomberg's People Data team in Princeton is seeking a Senior Data Management Professional who can transform how we acquire, onboard, maintain, and validate data through automation and AI-enabled workflows. You will design scalable data quality solutions, reduce manual effort, and collaborate with Data, Product, Enterprise, and Engineering to expand coverage and improve reliability.

This role offers a fast-paced, collaborative environment with opportunities to innovate across data, operations,