Senior Data Management Professional - Data Automation Engineer - People Data

AI in this role

nlp

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 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

We’d love to see:

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

Does this sound like you?Apply if you think we're a good match! We'll get in touch to let you know what the next steps are. Salary Range = 110,000 - 190,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.

We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

How we rate this

Senior Data Management Professional - Data Automation Engineer - People Data at Bloomberg rates 45 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.

Classification

Uses AI. An ordinary role that requires AI tools.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

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Skills and AI tools this role asks for

NLP

Questions you could be asked

What NLP problem have you worked on, and how did you measure whether it actually worked?
This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
Tell me about a time an AI tool got something wrong. How did you catch it?

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List these exact terms on your resume: NLP. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Put the AI tool in a bullet point about what you did, not just in a skills list — this role treats it as a required part of the job.

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