Senior Data Management Professional - Data Quality Engineer - Financials , NY P
Listed on 2026-02-28
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IT/Tech
Data Analyst, Data Engineer
Location: New York
Senior Data Management Professional - Data Quality Engineer - Company Financials
Description & RequirementsLocation
New York
Business Area
Data
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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.
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 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’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.
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 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
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)
Exposure to distributed systems like Spark
Background in statistics or machine learning
Experience with navigating complex data environments
Salary Range = 110000 - 190000 USD Annually + 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…
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