Venn Officer – Data Quality Assurance (DQA) – Raising The Village (RTV)

• Implement and strengthen Data Quality Assurance (DQA) frameworks across all survey activities.
• Conduct daily data quality checks to identify:
  • Duplicate records
  • Missing information
  • Data inconsistencies
  • Outliers
  • GPS anomalies
  • Unusually short interviews
• Monitor data quality indicators and prepare reports highlighting risks, trends, and recommendations.
• Escalate major data integrity issues and operational risks to the Senior Officer – Data Quality Assurance.
• Ensure compliance with organizational data quality standards and procedures.

• Manage audio audit processes by reviewing recordings and assessing adherence to survey procedures.
• Conduct field verification activities including:
  • Back-checks
  • Spot checks
  • Data validation exercises
• Select verification samples and reconcile findings with submitted data.
• Develop real-time monitoring dashboards tracking:
  • Survey progress
  • Enumerator performance
  • Data accuracy
  • Completeness and consistency
• Provide performance insights to improve field data collection activities.

• Develop automated data quality checks using tools such as:
  • Python
  • R
  • Data validation scripts
• Analyze survey metadata including:
  • Interview duration
  • GPS information
  • Enumerator activity patterns
  • Audit results
• Investigate causes of data quality problems and recommend corrective actions.
• Maintain a Data Quality Risk Register documenting recurring issues and improvement actions.
• Support continuous improvement of data collection systems and processes.

• Support development and improvement of Data Quality Assurance procedures and Standard Operating Procedures (SOPs).
• Create quality assurance tools, templates, and guidelines.
• Work with field operations, data management, and MEL teams to improve survey tools and processes.
• Support training initiatives that promote data literacy and quality standards.
• Promote a culture of accuracy, accountability, and evidence-based decision-making.

Required Qualifications and Experience

• Bachelor’s degree in:
  • Statistics
  • Data Science
  • Economics
  • Computer Science
  • Information Management
  • Any other quantitative discipline
• Minimum of 3 years’ professional experience in:
  • Data Quality Assurance
  • Data Management
  • Large-scale survey data collection
  • Development sector research projects
• Experience supporting household surveys or field-based evaluations.
• Demonstrated experience implementing data quality assurance processes throughout the survey lifecycle.

Required Technical Skills and Competencies

• Strong analytical and statistical skills.
• Ability to analyze large datasets and identify data quality issues.
• Experience conducting:
  • Data validation
  • Audio audits
  • Back-checks
  • Spot checks
  • Data verification exercises
• Proficiency in:
  • Python
  • R programming
  • Data cleaning and automation techniques
• Experience developing dashboards using:
  • Power BI
  • Looker Studio
  • Other business intelligence tools
• Strong knowledge of data management principles.
• Excellent problem-solving and reporting skills.
• Ability to communicate technical findings clearly to different audiences.

Salary Expectations

Benefits of Working with Raising The Village

• Opportunity to contribute to poverty reduction programs.
• Professional growth and development opportunities.
• Experience working with international development projects.
• Exposure to advanced data analytics and evidence-based programming.
• Collaborative and impact-driven work environment.

Career Growth Opportunities

• Senior Data Quality Officer
• Data Manager
• Monitoring, Evaluation and Learning (MEL) Specialist
• Data Analyst
• Research Manager
• Information Management Specialist
• Data Science Lead

How to Apply

Interview Preparation Tips

• Experience managing data quality assurance processes.
• Examples of improving data accuracy in field surveys.
• Experience using Python or R for data validation.
• Dashboard development and reporting experience.
• Handling large datasets and identifying errors.
• Experience working with NGOs, research organizations, or development programs.
• Approaches used to improve data collection processes.

CV Tips for Applicants

• Data quality assurance experience.
• Statistical analysis skills.
• Python, R, SQL, or data automation experience.
• Experience with Power BI or data visualization tools.
• Survey management experience.
• Monitoring, Evaluation and Learning (MEL) experience.
• Research and field data collection projects.
• Experience working with development organizations.