Senior Data Management Professional - Data Quality Engineer - Financials

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 innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes – all while providing platinum customer support to our clients.

Our Team:

The Company Financials team provides our clients with fast and accurate market‑moving data so they can stay on top of their game: broker estimates, financial filings, and any other dataset that is useful to understand financial performance in the markets. Our products run on intelligence and industry‑specific insights provided by our industry teams. We combine financial modeling, industry expertise, data management, and technical skills to curate critical metrics and drive insights from our data.

We are dedicated to crafting a best‑in‑class financial analysis and modeling product while constantly looking to enhance and expand our existing offering through a deep understanding of the markets we operate in and our clients’ current and future needs.

What’s the role?

The Company Financials team is looking for a Data Quality Engineer who is passionate about ensuring the integrity, accuracy, and reliability of data across complex systems. In this role, you will have the autonomy to investigate issues independently, build scalable solutions, and collaborate closely with data scientists, engineers, and business stakeholders.

You won’t just be identifying data problems; you’ll be solving them and taking them from proof‑of‑concept to scaling across our datasets. We want someone who takes full ownership of the quality of our data pipelines, develops robust validation systems, and leverages statistical thinking to anticipate and detect anomalies before they impact business decisions.

We’ll trust you to:

• Take ownership of data quality initiatives that span multiple critical data pipelines.
• Lead projects globally to improve data quality across all datasets under Company Financials.
• Harness both new and existing tools and systems for proactive data monitoring, validation, and anomaly detection.
• Use statistical techniques and identify machine‑learning opportunities to profile our data sets and find clear data inconsistencies or trends.
• Collaborate with a wide array of stakeholders across industries, product, engineering, and operations to solve problems at their root issues.
• Act as the point of escalation for systemic data quality issues; investigating, resolving, and preventing them independently, while balancing urgency with an aversion to technical debt.

You’ll need to have:

• A BA/BS degree or higher in Computer Science, Mathematics, or relevant data technology field, or equivalent professional work experience.
• 4+ years of Python programming and scripting in a production environment.
• 4+ years experience in data analysis, financial market research, and/or information technology.
• Sound understanding of data quality as a domain of data management (DAMA CDMP, DCAM certification a plus).
• Demonstrable ability to conduct data profiling and data analysis (using Python is a plus) and visualize results with tools such as python libraries, Qlik Sense or Tableau.
• Strong analytical abilities with a passion for data and evidence‑based decision‑making.
• Superb communication and project management skills; you can explain things to both technical and non‑technical audiences.
• Understanding of basic equity markets concepts and their application to financial data.
• Solid ability to combine technical skills with business insight.

We’d love to see:

• Master’s degree or equivalent experience or certification such as a CFA charter holder or CAIA.
• Experience with data observability platforms (e.g., Great Expectations, Soda).
• Background in statistics or machine learning.
• Experience with navigating complex data environments.

Salary Range = USD Annually+ Benefits + Bonus.

The referenced salary…