Data Enumerator at Hallmark Leadership Initiative (HALI)

Background

• Hallmark Leadership Initiative (HALI) is implementing a CBPF-funded Protection project titled: “Strengthening Disability-Inclusive Humanitarian Assistance in Maiduguri and Jere LGAs of Borno”.
• The project aims to enhance equitable, safe, and dignified access to humanitarian services for persons with disabilities.
• As part of implementation, HALI will conduct a baseline assessmentto establish benchmark data for key Protection, Disability Inclusion, AAP, CVA, and Health indicators.
• We are therefore seeking qualified and experienced Data Enumeratorsto support this baseline exercise.

Key Responsibilities
The Data Enumerator will:

• Participate in a mandatory pre-survey training.
• Administer structured questionnaires using KoboCollect / ODK.

Conduct interviews with:

• Persons with disabilities
• Leprosy-affected households
• Community members
• Ensure informed consent is obtained before interviews.
• Use disability-sensitive and inclusive communication approaches.
• Upload complete and accurate data daily.
• Ensure confidentiality and adhere to safeguarding principles.
• Respect Do No Harm, PSEA, and GBV-sensitive data collection standards.
• Report daily progress and field challenges to the M&E team.

Required Qualifications & Experience

• Minimum of SSCE
• Proven experience conducting Assessment (Data Collection)
• Experience using KoboCollect / ODK or similar mobile platforms.
• Experience working in humanitarian settings (Borno experience preferred).
• Ability to communicate fluently in English and relevant local language(s) (Kanuri, Hausa, etc.).
• Strong interpersonal and respectful engagement skills.
• Resident in Maiduguri or Jere (strongly preferred).

Preferred Competencies:

• Experience working with persons with disabilities or OPDs.
• Understanding of disability inclusion principles.
• Knowledge of safeguarding and Protection standards.
• Familiarity with AAP and feedback mechanisms.
• Experience in health-related or CVA-related data collection.