Nuveen is the investment management arm of TIAA. It is one of the largest global asset managers with specialist knowledge across a wide array of asset classes, including fixed income, equities and alternatives. Nuveen is driven not only by the independent investment processes across the firm, but also the insights, risk management, analytics and other tools and resources a truly world-class platform provides. As a global asset manager, our mission is to work in partnership with our clients to create outcome-focused solutions to help them secure their financial future. For more information about the firm please visit our website at
The DQ team is an integral part of the Nuveen Data Center of Excellence which operates as a Shared Services function under the umbrella of the Client Services & Technology Group. The team is a highly collaborative group of self-motivated individuals who work on various projects simultaneously with the goal of providing excellent service to our business partners and sound data to the organization.
Nuveen is seeking a talented individual who is passionate about the impact that data can have on an organization. The Data Quality Analyst is responsible to engage with data owners and stewards to elicit business rules and leverages traditional data quality tools to identify quality exceptions. Additionally, the Data Quality (DQ) team is seeking to implement various machine learning techniques to identify latent data quality concerns, both on an ad hoc basis and for production implementation.
As a member of the DQ team, the Data Quality Analyst is expected to represent the team on multiple projects with varying levels of complexity and duration. Additionally, the Data Quality Analyst will lead or participate in working groups within established projects, and suggest new initiatives based on what they observe, from hot spot issues to process improvements.
KEY RESPONSIBILITIES AND DUTIES:
Create business rules to manage Data Quality across the enterprise
Maintain Data Quality rules library
Profile data and recommend quality rules based on the results
Understand the fundamental data by domain to assist data stewards in resolving data quality exceptions
Utilize the exception management platform to track and manage data exceptions across various data domains and data sets
Triage exception management requests to determine severity
Investigate data errors and anomalies and assist in root cause analysis
Develop feedback loops and socialize data governance norms and best practices in discussions with data stewards
Become familiar with all domains and develop expertise in several domains
IT and Business Projects
Some or all of the following skills would be advantageous
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