Data Analyst, Data Engineering, AI Workflows

This is a fully remote position, open to applicants in Kenya.

📋 Description

• Clean, standardize, and validate extensive datasets, including farmer registrations, surveys, polygons, and photos.

• Conduct data quality assessments utilizing the gate-based DQC framework and SOPs, addressing flagged issues in collaboration with analysts and field teams.

• Reconcile gathered data with master lists and reference materials.

• Identify and rectify defects in data quality checks while recommending enhancements to SOPs.

• Develop and sustain ETL pipelines that transition data from collection tools and PostgreSQL/PostGIS databases to analysis outputs and client deliverables.

• Schedule and oversee automated jobs with logging, incremental loads, and failure notifications.

• Design and document data schemas, validation rules, and data dictionaries for country-specific projects.

• Write clean, version-controlled, and thoroughly tested Python and SQL code.

• Process geospatial data and assist with compliance checks, such as EUDR polygon validation.

• Establish and maintain AI-assisted workflows utilizing LLM tools for data cleansing, quality assessments, report generation, and repetitive analyst tasks.

• Create OCR and LLM-based document and image extraction pipelines with accuracy verification.

• Maintain prompts, reusable skills, project context files, and runbooks to ensure consistent and auditable AI workflows.

• Assess the performance of AI against deterministic scripts while monitoring cost, accuracy, and data privacy risks.

• Educate analysts on the safe and effective use of AI tools.

• Identify project risks and challenges, 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 provide training to analysts and field staff.

• Supply the manager with daily, weekly, and ad-hoc updates.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Statistics, Data Science, Information Systems, Economics, Geoinformatics, or a related field.

• At least 2 years of experience in data analysis or data engineering.

• Proven experience in cleaning large, messy field or survey datasets from start to finish.

• A portfolio, GitHub profile, or work samples demonstrating pipelines or automations created.

• Proficiency in Python, including pandas and automation scripting.

• Strong SQL skills, particularly with PostgreSQL.

• Experience in building and scheduling ETL pipelines.

• Familiarity with Git and working on Linux or cloud servers like AWS EC2.

• Practical experience using LLMs and AI tools within real workflows, including prompt design and accuracy checking of AI outputs.

• Knowledge of mobile data collection tools such as ODK, KoboToolbox, CommCare, or SurveyCTO.

• Experience with PostgreSQL; knowledge of PostGIS is a plus.

• Experience with R is an advantage.

• Familiarity with developing agentic or multi-step AI workflows, self-hosted/open-source models, OCR and document extraction techniques, geospatial tools, EUDR/deforestation compliance data, orchestration tools, or Docker is desirable.

🏝️ Benefits

• High-performance, multicultural team environment.

• Opportunities to engage in global agricultural insurance projects across Africa, Asia, and Latin America.

• Training for analysts and field staff on new systems and AI tools.

• Professional development opportunities through exposure to data engineering, geospatial data, AI workflows, and automation.