Data Manager at Policy Innovation Centre (PIC) Institute

The Policy Innovation Centre (PIC) Institute is at the forefront of a transformative movement to connect rigorous academic research with practical policymaking. As Africa's leading think tank, we understand that solving the continent's most pressing challenges requires innovative, evidence-based solutions. The PIC Institute is our answer to this need, creating a vibrant ecosystem where research meets action. The PIC Institute serves as a nexus for academics, policymakers, and stakeholders committed to fostering sustainable development in Africa. Leveraging the strengths of interdisciplinary research and real-world policy application, the institute champions innovative and impactful solutions across health, education, economic development, governance, and more. We are driven by a vision to address Africa’s complex societal challenges through collaboration, ensuring that policies are well-informed, human-centered, locally relevant, and grounded in robust evidence.

Job Summary

The PIC is seeking a Data Manager to oversee quantitative and qualitative datasets, ensure data integrity, clean data, and prepare datasets for analysis and reporting working closely with other members of the data analysis team.

Job Responsibilities

• Lead the management of quantitative and qualitative datasets from multiple sources, ensuring completeness, consistency, and reliability.
• Develop and maintain secure databases and data storage systems that meet organizational and donor data governance standards.
• Implement version control and backup procedures to safeguard data integrity and accessibility.
• Conduct comprehensive data cleaning, verification, and quality checks to identify and correct inconsistencies, errors, or duplicates.
• Apply validation rules and coding protocols to ensure standardized datasets across research and programme activities.
• Coordinate with field teams to resolve discrepancies and ensure timely submission of accurate data.
• Prepare datasets for analysis, ensuring appropriate labeling, formatting, and documentation of variables.
• Merge, transform, and organize data to meet analytical and reporting requirements.
• Develop and maintain metadata, data dictionaries, and codebooks for all project datasets.
• Work closely with data analysts, researchers, and monitoring teams to ensure smooth data flow from collection to reporting.
• Support the design and testing of data collection tools (e.g., electronic survey forms, mobile data systems).
• Provide technical assistance to project and field teams on data management procedures and best practices.
• Enforce data management protocols that comply with ethical standards and data protection regulations (including NDPR and GDPR where applicable).
• Conduct periodic audits to assess data quality, completeness, and adherence to research protocols.
• Maintain confidentiality and ensure restricted access to sensitive or personally identifiable information.
• Support the preparation of data-driven reports, dashboards, and visual insights for internal and external stakeholders.
• Ensure that data storage systems are efficient, secure, and user-friendly for the organization’s research and programme needs.
• Train project and field staff on data entry, cleaning, and quality assurance processes.
• Contribute to knowledge-sharing efforts by documenting best practices and lessons learned in data management.

Requirements

• Master’s degree in Statistics, Data Science, Computer Science, Economics, Demography, or other relevant quantitative or analytical field.
• Minimum of 5–8 years of professional experience managing large-scale quantitative and qualitative datasets within research or development programmes.
• Proven experience in data cleaning, validation, transformation, and preparation for analysis and reporting.
• Strong understanding of data management principles, database design, and data governance frameworks.
• Experience working with data management and analysis software such as Excel, Stata, SPSS, R, SQL, Power BI, or Python.
• Familiarity with digital data collection tools and platforms (e.g., KoboToolbox, SurveyCTO, ODK, etc).
• Demonstrated ability to ensure data integrity, security, and compliance with data protection regulations.
• Experience collaborating with research, M&E, and technical teams to align data workflows with project objectives.
• Strong analytical, organizational, and problem-solving skills, with keen attention to accuracy and detail.
• High professional integrity, commitment to confidentiality, and ability to manage multiple datasets under tight deadlines.

Benefits

• Competitive salary and benefits package.
• Professional development opportunities.
• A supportive and collaborative working environment.

Method of Application