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Monitoring & Evaluation (M&E) and Data Quality Assistant

Shelter For Life International2 open roles

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Your applicationOpen nowMonitoring & Evaluation (M&E) and Data Quality AssistantShelter For Life International
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This job: first seen 4 days ago

The posting

JOB DESCRIPTION

M&E and Data Quality Assistant

Organization

Shelter For Life International (SFL) is a Christian relief and development organization with over 30 years of experience providing humanitarian and development assistance to communities around the world. SFL's headquarters is located in Minnesota, USA. Our mission is to demonstrate God's love by enabling people affected by poverty, conflict, and disaster to restore their lives and rebuild their communities. SFL promotes socially and environmentally sustainable programming through cultural sensitivity, community participation, appropriate technologies, cost-effective methodologies, and human-centered design.

Learn more at www.shelter.org.

Project Overview

The United States Department of Agriculture (USDA) Foreign Agricultural Service, through its Food for Progress (FFPr) program, has awarded Shelter For Life a five-year (2023–2028) climate-smart horticulture value chain project called Cultivating Resilient and Optimal Production - Horticulture (CROP-H) in The Gambia.

The project has two strategic objectives:

  1. Increase agricultural productivity in horticultural products; and
  2. Expand trade of agricultural products domestically, regionally, and internationally through improvements in the trade-enabling environment.

Position Summary

The M&E Data Quality Assistant assists Shelter for Life's CROP-H M&E Manager to implement the CROP-H monitoring, evaluation, learning, and data management systems.

He/she will support data collection, data management, data quality assurance, indicator tracking, analysis, reporting, monitoring, and learning to ensure that project information is accurate, complete, timely, consistent, and supported by appropriate source documentation.

He/she will work closely with the technical teams, Regional Coaches, project partners, enumerators, and other relevant staff to generate reliable evidence for project monitoring, reporting, accountability, learning, and decision-making.

Key Responsibilities

1. M&E Planning and Data Collection

  • Support implementation of the project's M&E Plan, Performance Monitoring Plan (PMP), indicator tracking system, and data collection plans.
  • Support the M&E team in developing, reviewing, testing, updating, and standardizing data collection tools and methodologies in line with approved indicators, data sources, reporting requirements, and data quality standards.
  • Support baseline, midline, endline, routine monitoring, verification, and other surveys and assessments.
  • Implement approved data collection methodologies, sampling approaches, questionnaires, checklists, and field protocols.
  • Participate in field data collection, back-checks, spot checks, and verification exercises as required.
  • Support the preparation of data collection guidance and enumerator instructions.
  • Ensure that data collection tools capture required indicator information and appropriate disaggregation.

2. Data Management and Data Quality Assurance

  • Collect, enter, organize, clean, validate, and maintain project data in accordance with approved procedures.
  • Maintain accurate and organized datasets, databases, data files, and supporting documentation.
  • Operate and support approved digital data collection and management platforms.
  • Conduct routine data quality checks for accuracy, completeness, consistency, timeliness, validity, and duplication, as applicable.
  • Compare reported data with source documents and other supporting evidence to identify and resolve discrepancies.
  • Conduct routine data verification, spot checks, back-checks, and reconciliation exercises.
  • Support planning and implementation of Data Quality Assessments (DQAs).
  • Document DQA findings and support follow-up on corrective actions to address identified data quality gaps.
  • Maintain appropriate records of data corrections, validation checks, and verification activities.
  • Ensure that project data and supporting documentation are properly stored and handled in accordance with SFL data management and confidentiality requirements.

3. Indicator Tracking and Data Analysis

  • Support the M&E Manager in maintaining and updating the project's indicator tracking system.
  • Review reported indicator results against approved indicator definitions, targets, disaggregation requirements, data sources, and calculation methodologies.
  • Update monthly, semi-annual, annual, and indicator tracking tables as required.
  • Monitor progress against approved targets and identify data gaps, inconsistencies, or unusual changes in reported results.
  • Ensure that reported indicator results are supported by appropriate source documents and verifiable evidence.
  • Conduct routine analysis of project data to identify trends, progress, gaps, and emerging issues.
  • Support reconciliation of indicator results across databases, source documents, field records, and reporting templates.

4. Reporting and Data Visualization

  • Support preparation and compilation of monthly, quarterly, semi-annual, annual, and other project reports.
  • Coordinate M&E reporting inputs from relevant project teams and verify submitted data before inclusion in reports.
  • Prepare data tables, charts, graphs, dashboards, infographics, and other appropriate visualizations to communicate project performance and results.
  • Provide analytical summaries of project performance, data quality issues, progress, challenges, and follow-up actions.
  • Ensure that reported figures are consistent with approved indicator definitions and can be traced to supporting documentation.
  • Support preparation of evidence and data for donor reporting, management reviews, project learning, and other reporting requirements.

5. Monitoring, Learning and Capacity Building

  • Participate in routine field monitoring visits to verify implementation progress and reported results.
  • Support development and use of monitoring checklists and verification tools.
  • Document monitoring findings, data quality issues, agreed actions, and follow-up requirements.
  • Support documentation of lessons learned, good practices, case studies, and success stories.
  • Participate in learning and reflection activities and communicate relevant M&E findings to project teams.
  • Assist in organizing and facilitating training and orientation for project staff, enumerators, Regional Coaches, and partners on data collection, data quality, digital tools, indicator definitions, and reporting procedures.
  • Provide technical support to data collectors and project staff on the proper application of approved M&E tools and procedures.
  • Support refresher training when data quality issues or changes to tools and methodologies are identified.

6. M&E Documentation and Coordination

  • Maintain organized electronic and hard-copy M&E records, including datasets, data collection tools, indicator tracking tables, monitoring reports, DQA records, source documents, and reporting submissions.
  • Apply appropriate file naming, version control, documentation, and data storage practices.
  • Maintain an organized M&E repository to facilitate data retrieval, verification, reporting, learning, and audit requirements.
  • Coordinate regularly with the M&E Manager, technical teams, Regional Coaches, and project partners to ensure timely submission and validation of M&E information.
  • Support external evaluations, assessments, audits, and other evidence-generation activities, including preparation of data and supporting documentation.
  • Perform other related M&E, data quality, monitoring, assessment, and reporting duties assigned by the M&E Manager.

Qualifications and Skills

Education

  • Bachelor's degree in Monitoring and Evaluation, Statistics, Economics, Social Sciences, Development Studies, Agricultural Economics, Data Management, or a related field.
  • Additional training in monitoring and evaluation, data management, statistics, research methods, or related areas is an advantage.

Experience

  • At least two years of relevant professional experience in monitoring and evaluation, data management, data quality assurance, research, or a related field, preferably in humanitarian, development, agriculture, or donor-funded programs.
  • Demonstrated experience in data collection, data cleaning, verification, analysis, reporting, and documentation.
  • Experience with digital data collection platforms and databases.
  • Experience supporting surveys, assessments, data quality assessments, field monitoring, or evaluations is an advantage.
  • Experience working with donor-funded projects is an advantage.

Technical Skills

  • Good understanding of monitoring and evaluation principles, indicator tracking, data quality assurance, data collection methodologies, and results-based management.
  • Strong proficiency in Microsoft Excel, including data cleaning, validation, formulas, pivot tables, analysis, and data visualization.
  • Experience with mobile/digital data collection platforms such as KoboToolbox, ODK, SurveyCTO, ActivityInfo, or equivalent platforms.
  • Familiarity with statistical or data analysis software such as SPSS, Stata, R, and business intelligence and data visualization platform such as Power BI, or equivalent tools is an advantage.
  • Ability to develop, review, manage, and maintain structured data collection tools and datasets.
  • Ability to prepare clear tables, charts, dashboards, and other data visualizations.
  • Understanding of data confidentiality, secure data management, and appropriate handling of sensitive project information.
  • Strong analytical, organizational, problem-solving, and attention-to-detail skills.

Communication and Interpersonal Skills

  • Excellent written and verbal communication skills in English.
  • Knowledge of local languages is an asset.
  • Ability to communicate M&E and data quality findings clearly to technical and non-technical audiences.
  • Strong interpersonal skills and ability to work effectively with multidisciplinary and multicultural teams.
  • Ability to coordinate effectively with project staff, partners, enumerators, and field teams.

Personal Attributes

  • Strong commitment to data accuracy, integrity, accountability, confidentiality, and quality.
  • High attention to detail and ability to work systematically with data and supporting documentation.
  • Proactive approach to identifying, investigating, and resolving data quality issues.
  • Ability to manage multiple priorities and meet reporting deadlines.
  • Willingness and ability to travel regularly to field sites, including rural and hard-to-reach areas, as required.
  • Commitment to SFL's mission, values, and principles of community participation, accountability, and responsible development.

How to Apply:

Interested candidates who meet the qualifications are invited to apply by clicking Apply Here. Please ensure to submit your CV and a short cover letter through the application portal. Kindly note that applications sent by email will not be considered.

Application Deadline:

  • Please submit your application by October 27, 2026. Any applications submitted after this deadline will not be considered.
  • Note: We appreciate your interest in joining the Shelter for Life team. We will review applications carefully and only contact shortlisted candidates for interviews.
  • Shelter for Life International is an equal-opportunity employer and encourages female candidates and individuals from all backgrounds to apply.



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