Data Analyst, Data Engineering, AI Workflows

• Clean, standardise and validate large field datasets including farmer registrations, surveys, polygons and photos
• Run data quality checks using the gate-based DQC framework and SOPs, and resolve flagged issues with analysts and field teams
• Reconcile collected data against master lists and reference data
• Identify and correct defects in data quality checks and recommend SOP improvements
• Build and maintain ETL pipelines from collection tools and PostgreSQL/PostGIS databases to analysis outputs and client deliverables
• Schedule and monitor automated jobs with logging, incremental loads and failure alerts
• Design and document data schemas, validation rules and data dictionaries for country projects
• Write clean, version-controlled and tested Python and SQL
• Process geospatial data and support compliance checks such as EUDR polygon validation
• Set up and maintain AI-assisted workflows using LLM tools for data cleaning, quality checks, report drafting and repetitive analyst tasks
• Build OCR and LLM-based document and image extraction pipelines with accuracy verification
• Maintain prompts, reusable skills, project context files and runbooks for consistent, auditable AI workflows
• Evaluate AI versus deterministic scripts and track cost, accuracy and data privacy risks
• Train analysts to use AI tools safely and effectively
• Identify project risks and issues, propose practical solutions, and prepare dashboards, reports and delivery files
• Develop and evaluate operational processes and procedures
• Draft technical documentation, SOPs and training materials, and train analysts and field staff
• Provide the manager with daily, weekly and ad-hoc updates

• Bachelor’s degree in Computer Science, Statistics, Data Science, Information Systems, Economics, Geoinformatics, or a related field
• Minimum of 2 years of experience in data analysis or data engineering
• Demonstrated experience cleaning large, messy field or survey datasets end to end
• Portfolio, GitHub profile or work samples showing pipelines or automations built
• Strong Python, including pandas and scripting for automation
• Strong SQL, with experience in PostgreSQL
• Experience building and scheduling ETL pipelines
• Experience using Git and working on Linux or cloud servers such as AWS EC2
• Hands-on experience using LLMs and AI tools in real workflows, including prompt design and checking AI outputs for accuracy
• Familiarity with mobile data collection tools such as ODK, KoboToolbox, CommCare, or SurveyCTO
• Experience with PostgreSQL; PostGIS is a plus
• Experience with R is a plus
• Experience building agentic or multi-step AI workflows, self-hosted/open-source models, OCR and document extraction, geospatial tools, EUDR/deforestation compliance data, orchestration tools or Docker is nice to have

• High-performance, multicultural team environment
• Opportunities to work on global agricultural insurance projects across Africa, Asia and Latin America
• Training analysts and field staff on new systems and AI tools
• Professional development through exposure to data engineering, geospatial data, AI workflows and automation