Head of Data Quality Systems

. Set data quality standards for farmer registries, including completeness, verification evidence, and program targets .

Posted 10/23/2026full-timeRemote • KenyaLeadWebsite

Tools & technologies

PythonSQL

Key responsibilities & impact

Set data quality standards for farmer registries, including completeness, verification evidence, and program targets
Design data quality architecture covering collection-app validation rules, record-arrival pipelines, anomaly detection, and dashboards
Build the matching layer linking records to national ID, land, and other government databases
Develop deduplication logic
Design verification systems for back-checks, phone verification, and audits, including sampling, scoring, and follow-up
Partner with Product to embed quality rules in the collection app
Partner with Field Operations on enumerator payment, supervision, and training processes
Make the data quality system reusable for every new registry
Own data quality presentations to government clients and lead senior-level discussions
Ensure compliance with data protection laws in each operating country
Hire, lead, and develop analysts and engineers responsible for daily checks, audits, and reporting
Establish a unified quality framework and system design across registries
Launch and maintain the core system across active programs with weekly quality reports for project leads
Use AI models such as OCR, face matching, and large language models to automate checks while ensuring appropriate human review, accuracy, and fairness

What you’ll need

8 or more years in data quality, data engineering, or survey operations
At least 4 years leading teams
Track record of designing and building data quality systems at scale, including automated validation pipelines, anomaly detection, and record linkage
Experience owning data quality for national-scale field collection with 500,000 or more records
Experience building and leading a team responsible for day-to-day quality checks and audits
Strong SQL and Python or R skills sufficient to set technical direction and review team work
Understanding of mobile collection tools such as ODK, SurveyCTO, KoBo, or CommCare
Understanding of how form design affects data quality
Clear English and ability to explain data to non-technical people, including senior government officials
French is a strong advantage
Experience with digital public infrastructure, ID systems, or World Bank or donor-funded registries is advantageous
Experience with geospatial data, including GPS points and farm boundaries, is advantageous
Experience with agriculture or smallholder farmer programs in Africa is advantageous

Comp & perks