Senior Data Analyst

Sr. Analyst / AI Engineer

Location: LATAM Remote, US business hours

Overview:

We are seeking a hands-on Sr. Analyst / AI Engineer to help automate and optimize operations across the business using Python, SQL, AI tools, and data workflows. This person will work closely with the team to improve internal processes, strengthen data infrastructure, and build practical automation solutions that reduce manual work and improve decision-making.

The ideal candidate is highly organized, fast-moving, and comfortable working in a dynamic environment where processes are still being built and refined. They should be able to quickly understand existing workflows, identify problems, and turn them into reliable, scalable systems.

Key Responsibilities:

• Maintain, improve, and expand existing Python automations.
• Analyze current operational workflows and identify opportunities for automation.
• Build and support data processes using SQL, AWS, and virtual machine environments.
• Organize and structure data so non-technical users can access and use it more easily.
• Work heavily in Excel to support operational analysis and endpoint workflows.
• Document processes clearly and create maintainable, repeatable systems.
• Troubleshoot broken workflows and quickly identify root causes.
• Support ERP and CRM-related tasks, including Odoo.
• Collaborate with internal stakeholders on shipments, pricing checks, reporting, and operational reviews.
• Use AI tools, including Claude, to accelerate automation and process improvement efforts.

Required Qualifications:

• Strong experience with Python automation.
• Solid Excel skills and comfort working with large spreadsheets and operational data.
• Experience with SQL and data organization.
• Familiarity with AWS and virtual machine environments.
• Experience working with ERP and/or CRM systems.
• Strong organizational skills and ability to manage multiple tasks at once.
• Ability to understand business processes quickly and act decisively.
• Excellent communication skills and comfort working with both technical and non-technical stakeholders.
• Experience with GitHub or similar version control tools.

Preferred Qualifications:

• Experience in data engineering, analytics, or operations automation.
• Familiarity with Claude or other AI tools for workflow automation.
• Experience building interfaces or tools for non-technical users.
• Background in process optimization, infrastructure support, or operational systems.
• Exposure to Odoo or similar ERP platforms.
• Experience working in environments where processes are still being built out.

Success in the Role:
First 30 Days: Learn the environment, understand current automations, and become familiar with the team's workflows and pain points.

By 60 Days: Begin improving existing automations, organizing data more effectively, and helping streamline repetitive tasks.

By 90 Days: Independently identify issues, propose improvements, and contribute to a more scalable automation and data infrastructure.

Ideal Candidate Profile:
The ideal candidate is a hybrid between a data analyst and a data engineer, with strong process intuition and the ability to move quickly. They should be comfortable building in a hands-on environment where structure is still evolving and where they will help shape the future workflow architecture.