Senior Data Management Professional - Data Automation Engineer - People Data

Bloomberg•Princeton, FL

About The Position

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.

Requirements

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 designing and implementing automation solutions that eliminate manual workflows and improve operational scalability
Experience writing production-ready code and conducting unit and/or integration testing
Strong Python skills with experience building production-grade data workflows, automation solutions, and analytical tooling
Understanding of Data Engineering best practices
Superb communication and project management skills
Solid ability to combine technical skills with business insight

Nice To Haves

DAMA CDMP or DCAM certification
Experience designing human-in-the-loop workflows for data review, exception handling, or quality control
Agile/Scrum Project Management experience
Experience using data analysis and visualization tools such as Tableau or QlikSense
Experience with financial data, people data, company data, private markets data, corporate governance data, or executive and board datasets

Responsibilities

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