Department/Group: VENN
Reporting To: Senior Officer- Data Quality Assurance
Years of Experience 3+ Years
Location: Mbarara
Travel Required: 20%

About Raising The Village
At Raising The Village (RTV), we are dedicated to eradicating ultra-poverty in Sub-Saharan Africa. As a dynamic, rapidly growing international development organization, we’ve assembled a team of over 350+ passionate individuals in Uganda, Rwanda, Tanzania and DRC, alongside an additional 10+ professionals in North America. Together, we are committed to elevating communities out of ultra-poverty by implementing innovative solutions and leveraging advanced data analytics to drive impact.

To date, our holistic approach has positively impacted over 1,000,000 lives since 2012, and we’re poised to achieve even greater milestones, aiming to assist 1 million individuals annually by 2027. Our growth and success are fuelled by the invaluable support of global partners who share our vision of sustainable change. Learn more about our impactful programs at www.raisingthevillage.org

Purpose of the role
The Data Quality Assurance (DQA) Officer is responsible for safeguarding the quality, integrity, and reliability of Raising The Village's (RTV) primary data from survey design and field preparation to data collection, monitoring, validation, and reporting. The role leads operational data quality assurance for all RTV field-based evaluation surveys, including baseline, midline, endline, routine monitoring, and special studies for all countries of operation. This is a highly analytical and hands-on role requiring continuous interrogation of incoming datasets, implementation of automated quality assurance processes, monitoring enumerator performance using survey metadata, conducting root-cause analyses of data quality issues, and translating findings into timely corrective actions that improve field performance and data reliability.

Key Responsibilities

1. Data Quality Governance

• Implement and continuously strengthen RTV's Data Quality Assurance (DQA) Frameworks across all survey activities.
• Conduct daily data quality assessments to identify duplicates, outliers, missing data, logical inconsistencies, unusually short interviews, GPS anomalies, and other quality issues, ensuring rapid feedback to field teams.
• Monitor and report Data Quality Assurance KPIs at the conclusion of each data collection activity, highlighting risks, trends, and recommendations.
• Escalate significant data quality risks, integrity concerns, or survey implementation issues to the Senior Officer Data Quality in a timely manner.

2. Field Monitoring, Verification, and Audits

• Manage the end-to-end audio audit process by ensuring proper review of recordings, assessing enumerator adherence to survey protocols, documenting findings, and recommending corrective actions.
• Coordinate and oversee field verification activities, including back-checks and spot checks, by selecting verification samples, managing review tools, reconciling findings with original submissions, and escalating discrepancies.
• Develop and maintain real-time field monitoring dashboards tracking survey progress, enumerator productivity, and key data quality indicators including accuracy, completeness, consistency, validity, and timeliness.
• Produce regular enumerator and team performance analyses to support targeted coaching and real- or near real-time performance improvement.

3. Data Automation, Analytics, and Root-Cause Analysis

• Design, develop, automate, and maintain data quality pipelines using R, Python, or other analytical tools to systematically validate incoming survey data and generate monitoring outputs.
• Analyze survey metadata including interview duration, navigation patterns, GPS records, audit findings, and verification results to identify data quality risks and determine underlying causes.
• Conduct root-cause investigations to distinguish between tool design issues, process weaknesses, enumerator performance challenges, or systemic operational problems, and recommend practical corrective actions.
• Maintain the organizational Data Quality Risk Register by documenting recurring issues, mitigation actions, and lessons learned to strengthen future survey implementation.

4. Standards, Documentation, and Capacity Strengthening

• Support the development, documentation, implementation, and continuous improvement of Standard Operating Procedures (SOPs), quality assurance protocols, and organizational data quality standards aligned with industry best practices.
• Develop and maintain standardized quality assurance tools, templates, and guidance documents supporting consistent implementation across projects.
• Collaborate closely with field operations, data management, and MEL teams to incorporate lessons learned into survey tools, quality assurance processes, field protocols, and training materials.
• Promote organizational data quality culture by supporting initiatives that strengthen data literacy, compliance with data governance standards, and continuous learning across technical teams.

Qualification and Experience

Education

• Bachelor's degree in Statistics, Data Science, Economics, Computer Science, Information Management, or another quantitative discipline.

Experience

• Minimum of three (3) years of professional experience in Data Quality Assurance, Data Management supporting large-scale primary data collection.
• Demonstrated experience supporting household surveys or other large-scale field-based data collection within the development sector.
• Proven experience implementing data quality assurance processes across the survey lifecycle.

Technical Competencies

• Strong analytical and statistical skills with demonstrated ability to profile large datasets, detect anomalies, validate data, and investigate root causes of quality issues.
• Practical experience implementing and managing audio audits, back-checks, spot checks, and related verification methodologies.
• Proficiency in R, Python, or data cleaning, validation scripting, automation, and statistical analysis.
• Experience developing interactive dashboards using Power BI, Looker Studio, or equivalent business intelligence tools.

• Implement and continuously strengthen RTV's Data Quality Assurance (DQA) Frameworks across all survey activities.
• Conduct daily data quality assessments to identify duplicates, outliers, missing data, logical inconsistencies, unusually short interviews, GPS anomalies, and other quality issues, ensuring rapid feedback to field teams.
• Monitor and report Data Quality Assurance KPIs at the conclusion of each data collection activity, highlighting risks, trends, and recommendations.
• Escalate significant data quality risks, integrity concerns, or survey implementation issues to the Senior Officer Data Quality in a timely manner.
• Manage the end-to-end audio audit process by ensuring proper review of recordings, assessing enumerator adherence to survey protocols, documenting findings, and recommending corrective actions.
• Coordinate and oversee field verification activities, including back-checks and spot checks, by selecting verification samples, managing review tools, reconciling findings with original submissions, and escalating discrepancies.
• Develop and maintain real-time field monitoring dashboards tracking survey progress, enumerator productivity, and key data quality indicators including accuracy, completeness, consistency, validity, and timeliness.
• Produce regular enumerator and team performance analyses to support targeted coaching and real- or near real-time performance improvement.
• Design, develop, automate, and maintain data quality pipelines using R, Python, or other analytical tools to systematically validate incoming survey data and generate monitoring outputs.
• Analyze survey metadata including interview duration, navigation patterns, GPS records, audit findings, and verification results to identify data quality risks and determine underlying causes.
• Conduct root-cause investigations to distinguish between tool design issues, process weaknesses, enumerator performance challenges, or systemic operational problems, and recommend practical corrective actions.
• Maintain the organizational Data Quality Risk Register by documenting recurring issues, mitigation actions, and lessons learned to strengthen future survey implementation.
• Support the development, documentation, implementation, and continuous improvement of Standard Operating Procedures (SOPs), quality assurance protocols, and organizational data quality standards aligned with industry best practices.
• Develop and maintain standardized quality assurance tools, templates, and guidance documents supporting consistent implementation across projects.
• Collaborate closely with field operations, data management, and MEL teams to incorporate lessons learned into survey tools, quality assurance processes, field protocols, and training materials.
• Promote organizational data quality culture by supporting initiatives that strengthen data literacy, compliance with data governance standards, and continuous learning across technical teams.

• Strong analytical and statistical skills
• Ability to profile large datasets, detect anomalies, validate data, and investigate root causes of quality issues.
• Practical experience implementing and managing audio audits, back-checks, spot checks, and related verification methodologies.
• Proficiency in R, Python, or data cleaning, validation scripting, automation, and statistical analysis.
• Experience developing interactive dashboards using Power BI, Looker Studio, or equivalent business intelligence tools.

• Bachelor's degree in Statistics, Data Science, Economics, Computer Science, Information Management, or another quantitative discipline.