Data Quality and Research Administration Analytics Manager

Khoury College; Toronto; On-site; CAD 80,000 - 100,000; Full time

Job summary

A leading university is seeking a Data Quality and Research Administration Analytics Manager to enhance data governance strategies and improve data quality across research applications. The role involves client engagement, managing data quality, project management, and collaboration with various university stakeholders to foster an environment of operational excellence and data-driven decision-making.

Qualifications

• Minimum 5 years of experience with data quality and information system management.
• Experience in research administration and regulations.
• Ability to implement continuous improvement and innovation tools.

Responsibilities

• Conduct data quality analysis to resolve issues and maximize analytics value.
• Collaborate on reporting analytics and define data quality rules.
• Oversee data governance documentation and communication processes.

Skills

Data analysis

Leadership

Problem-solving

Effective communication

Education

Bachelor's degree in Computer Science, Information Systems or related field

Tools

Microsoft Suite

Tableau

SQL

Cognos

Job description

Under the supervision of the Northeastern University Research Enterprise Services (NU-RES) Director of Research Operations and Systems and with support of senior level NU-RES team members, the Data Quality and Research Administration Analytics Manager (“Data Manager”) is responsible for developing and executing local data governance strategies, managing data quality, building and driving digital initiatives that support the research enterprise, and improving the analytical value of data related to the university’s research enterprise. They will focus on client engagement and internal operational efficiencies to implement data governance policies, procedures, processes, and standards and work with a variety of university partners to identify opportunities to improve data quality across the university’s global research network.

The Data Manager is responsible for information system management and best practice standards to improve data quality across NU-RES applications (e.g., eCD eCLAWs ePAWs), which includes analyzing data collection workstreams, creating processes and procedures, recommending new policies, and monitoring the collection and storage of NU-RES data; they will work closely with the NU-RES Director of Research Operations and Systems and eRA Systems Manager on implementing NU-RES’s digital strategy through evaluation of enterprise data standards, technology, and processes.

The Data Manager is responsible for educating and training end-users on sound data quality standards and internal control practices, fostering a culture of quality client service; assessing and interpreting data in support of operational excellence and data-driven decision making by senior leadership.

The Data Manager will evaluate how digital governance of research data impacts data quality and will work to maximize the value of analytics and innovation to transform the university’s data reporting capabilities, while encouraging the adoption of contemporary methods, practices, and measurement outcomes, producing consistent and accurate information.

This position requires a high level of competence with research administration (including regulatory requirements related to research and sponsored programs) and information technology; excellent analytical skills with ability to work with large and complex data sets; strong leadership and project management skills; experience in creating and executing local data governance policies, procedures, processes, and standards; an ability to facilitate communication between and among groups that may have different needs and priorities. The Data Manager must have a strong commitment to creating positive client experiences and supporting individuals who work in a fast-paced, team-oriented environment.

Minimum Qualifications

Bachelor's degree in Computer Science, Information Systems or related field.

A minimum of (5) years of experience with data quality, data analysis and information system management.

Experience and understanding of research administration and regulations related to research and sponsored programs.

Demonstrated ability to implement continuous improvement and innovation tools and techniques.

Excellent analytical, curiosity, problem-solving, and effective written and verbal communication skills.

Proficient IT skills with Microsoft Suite, Tableau, SQL, and Cognos

Key Responsibilities & Accountabilities

40% - Data Quality Analysis : Use data analysis to identify data quality issues and determine how to solve them. Analyze data utilized by cross-functional teams to ensure data integrity, recognize, analyze trends and / or anomalies; maximize the value of accurate analytics to transform the university’s research reporting capabilities; design data quality standards for research data and develop a best practice to align best the most accurate and consistent outcome of information.

30% - Reporting Analytics : Collaborate with Senior Data Analyst to identify appropriate categories of data, summarize and analyze in custom ad hoc reports. Through Critical Thinking, analyze the data usage by performing assessments on data end-to-end. Define and design the data quality rules by understanding the needs and demands from user community.

15% - Digital Governance, Improvement and Training : Troubleshoot discrepancies and delegate to the appropriate personnel for correction. Consult with functional and technical staff and data stewards about meaning, use, reliability, and maintenance of data elements. Contribute to continuous process improvement in report analysis and trending methods. Manage and maintains all data governance and data quality related documentation. Establish the effective data quality rules by ensuring data validity, conformity, completeness, and timeliness.

15% - Project Management : Oversee the completion of tasks or projects. Define business rules for measuring data quality and profiling new data sources. Work with data engineers to enhance and refine data quality metrics. Use effective communication to convey messages, explain processes, and answer questions.