Data Analyst

Role Overview

• Lead end-to-end execution of assigned agricultural data projects, from data quality checks through final client deliverables.
• Create and monitor data quality checks using established DQC frameworks, ensuring data integrity across all project phases.
• Produce project-specific reports, analyses, and dashboards for client and internal consumption.
• Manage and assign daily tasks to one Junior Data Analyst, ensuring timely completion and quality of work.
• Step in to execute DQCs directly when necessary.
• Own all client-facing deliverables for assigned projects (subject to peer and management review).
• Manage field team orientation and training on DQC frameworks for assigned projects.
• Design and build Amazon QuickSight dashboards for all team projects, regardless of project lead assignment.
• Create and maintain reusable dashboard templates, visualization standards, and reporting best practices.
• Define and enforce formatting standards for all team reports and client-facing analytics outputs.
• Peer-review reports and visualizations produced by other team analysts to ensure consistency and quality.
• Serve as the team’s final authority on analytics and dashboard quality standards.
• Maintain the Analytics & Reporting Knowledge Base as a living resource for the team.
• Train the entire team on QuickSight and visualization tools and best practices.
• Build automated reporting pipelines to reduce manual effort and improve consistency.
• Review DQC execution, reports, and analyses produced by peer analysts on their projects.
• Accept reciprocal review of your own work by the Associate Manager or peer analyst.
• Directly mentor the Junior Data Analysts.

Requirements

• Bachelor’s degree in Data Science, Statistics, Computer Science, Actuarial Science, Economics, or a related quantitative field.
• 3+ years of experience in data analysis, business intelligence, or a related analytical role.
• Demonstrated proficiency in SQL and at least one programming language (Python or R) for data manipulation and analysis.
• Hands-on experience building dashboards and visualizations using BI tools (Amazon QuickSight, Tableau, Power BI, or similar).
• Strong understanding of data quality principles, validation logic, and data cleaning workflows.
• Experience producing client-facing reports and analytical deliverables with high attention to detail.
• Excellent written and verbal communication skills, with the ability to translate complex data into clear insights.

Tech Stack

• Python
• SQL
• Tableau

Benefits

• Health insurance
• Paid time off
• Flexible work arrangements
• Professional development