Senior Data Management Professional - Data Automation Engineer - Data

Senior Data Management Professional
- Data Automation Engineer
- People Data Description & Requirements

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 workflow efficiencies, and we implement technology solutions to improve our systems, products, and processes.

The People Data team provides our clients with a unique dataset of corporate executives, directors, and individuals moving the market to identify risks and opportunities via unconventional financial analysis. Factors including corporate governance, executive pay for performance, leadership changes, career history, and corporate diversity have become a crucial piece to forming business decisions with deeper company intelligence.

The Role:

The People Data team is looking for a highly motivated individual with a passion for data, operations, and technology to build and optimize our data product by evolving our data quality and acquisition systems. As a Senior Data Management Professional, you will help improve the quality, breadth, and scalability of People Data by transforming how we acquire, onboard, maintain, and validate data through automation and AI-enabled workflows.

This role is ideal for someone who enjoys identifying inefficient processes, designing practical solutions, and driving implementation from concept through production. You will work across data, operations, and technology to build scalable systems that reduce manual effort, improve data quality, and accelerate coverage expansion.

We’ll trust you to:

• Design and implement scalable solutions to improve data quality, automate data acquisition, and expand coverage across the People Data product
• Identify recurring manual processes, operational bottlenecks, and quality failure points, then translate them into automation opportunities and preventive controls
• Design, build, and deploy automation solutions that improve data quality, expand coverage, and scale data onboarding and maintenance across datasets
• Investigate complex operational challenges and independently develop scalable solutions that reduce manual effort and improve data reliability
• Perform data profiling and apply analytical methods to support data quality measurements, rulesets, and monitoring frameworks
• Collaborate with domain experts in Data, as well as colleagues in Product, Enterprise, and Engineering, to design and implement solutions that improve data quality and scale acquisition systems
• Design and implement AI-enabled workflows to classify, extract, enrich, reconcile, validate, and prioritize People Data at scale
• Define success metrics to measure automation impact, data quality improvement, operational efficiency, and coverage expansion
• Educate and empower colleagues on data quality, automation, and scalable data management principles
• Keep up with industry trends, standards, and innovation across data quality, data operations, AI, and engineering domains
• Work in a fast-paced, multifaceted, and collaborative setting

You’ll need to have:

• A BA/BS degree or higher in Computer Science, Mathematics, Information Systems, Finance, or a related field, or equivalent professional work experience
• 3+ years of professional experience in Data Quality Management, Data Management, Data Operations, Data Acquisition, Data Governance, or related disciplines within Finance or Technology industries
• Experience applying AI, machine learning, NLP, or rules-based automation to data acquisition, enrichment, validation, or operational workflows
• Experience developing data quality metrics and business rules as part of a broader data architecture or operational framework
• Understanding of data pipelines, workflow orchestration, and automation frameworks used to acquire, transform, and maintain data at scale
• Experience identifying workflow inefficiencies and partnering with technical teams to deliver scalable data solutions
• Demonstrated experience…