Data Analyst - Agriculture Sector

Linah Group Open · verified Oct 24, 2026

On-site Bahariya Oasis Full-time Mid-level Data Analysis & BI

At a glance

Mid-level Data Analysis & BI role at Linah Group. Bahariya Oasis · full-time.

Pay not stated Data Analyst salary

RoleData Analysis & BI

SeniorityMid-level

LocationBahariya Oasis

WorkplaceOn-site

EmploymentFull-time

PostedSep 3, 2026 · 7w ago

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Keep the Historical Farm Profile current by checking records from field engineers against lab results
Turn farm measurements on yield, soil, irrigation, inputs and weather into clean datasets for analysis
Measure costs, yields and intervention returns against farm baselines, including recommendations, technology and training
Prepare dashboard data and reports that show farm performance, program progress and plain-language findings
Spot regional pest or climate patterns for R&D and technical teams, and refine reporting methods with feedback

What you bring

A bachelor’s degree in data science, statistics, agricultural economics or a related listed field
At least three years analyzing data, ideally in agriculture, agtech or another listed sector
Strong Excel skills, plus experience with an analytics or BI platform such as Power BI or Tableau
Working SQL knowledge for querying and maintaining databases, along with a grasp of basic farm metrics

Who this fits

This role suits a mid-level analyst who can turn agricultural data into clear findings for both technical and non-technical audiences. It is based on-site in Bahariya Oasis, Egypt.

From the employer

Position Summary:

Linah is looking for a detail-oriented Data Analyst to turn raw agricultural field data into clear, actionable insight. The data analyst will be the bridge between what happens on client farms and the decisions made by both clients and Linah's technical support department — processing field metrics, building performance reports, flagging risks early, and quantifying the return on investment (ROI) of Linah's interventions.

Job Duties & Responsibilities:

Build and maintain the "Historical Farm Profile" database, ensuring all data from field engineers and lab results are accurately and consistently recorded

Collect, clean, and validate agricultural data gathered from client farms (yield, soil health, irrigation, inputs usage, weather, crop cycles, etc.)
Process and structure raw field data into usable datasets for analysis
Calculate cost vs. yield metrics, tracking how Linah's interventions impact the client's bottom line
Calculate and track the broader ROI of Linah's interventions (e.g., input recommendations, technology adoption, training programs) against baseline performance
Prepare the data that feeds into the Client Digital Dashboard, including implementation rates and technical program progress
Build dashboards and visualizations that clearly communicate farm performance trends over time
Analyze trends across different regions to provide the R&D and Technical teams with early warnings about pest outbreaks or climate impacts
Design and generate the standardized, logic-based technical reports delivered to clients
Prepare regular performance reports for clients and internal management, translating technical data into plain-language insights
Collaborate with field agronomists/engineers to ensure data collected is accurate, complete, and relevant
Maintain data quality standards and documentation for all datasets, databases, and reporting processes
Support management with ad hoc data requests and predictive analysis for planning and forecasting
Continuously improve reporting templates, dashboards, and analytical methods based on client and management feedback

Requirements

Bachelor's degree in Data Science, Statistics, Agricultural Economics, Agronomy, Computer Science, or a related field
3+ years of experience in data analysis, ideally within agriculture, agtech, or FMCG, or supply chain sectors
Strong proficiency in Excel and at least one analytics/BI tool (e.g., Power BI, Tableau, Looker)
Working knowledge of SQL for data querying, database maintenance, and manipulation
Experience with Python or R for data processing/analysis is a plus
Ability to build clear, digestible dashboards and reports for both technical teams and non-technical audiences
Strong understanding of basic agricultural concepts (crop cycles, yield metrics, farm inputs) or willingness to learn quickly
Excellent analytical thinking and attention to detail
Strong communication skills — able to translate numbers into a story for clients and management

Benefits