Data Services Manager (Mexico City) — AI-Driven Lead

Open CEDA; Ciudad de México; Hybrid; MXN 1,800,000 - 3,000,000; Full time

Job summary

Watershed in Mexico City is seeking a Manager for our Customer Data Services team. You will lead a seven-person Data Specialists group, drive quality and efficiency, and shape capabilities for enterprise clients.

This role focuses on coaching, operational excellence, and cross-functional collaboration to deliver high-value data services. You will own strategic initiatives, champion AI-enabled workflows, and ensure rigorous data practices while fostering an inclusive, high-performance culture in

Qualifications

• 8+ years of professional experience in data/services or related field.
• 2+ years of demonstrated success managing a services, operations, or customer-facing team.

Responsibilities

• Lead and develop a high-performing Data Specialists team in the Mexico City office.
• Own team quality, responsiveness metrics, and review habits to ensure error-free output.
• Coach team on communication and customer-facing skills; cover customer calls when needed.
• Drive day-to-day team operations: prioritize work, manage capacity, and remove blockers.
• Support data problem solving and scale solutions; guide use of appropriate tools.
• Own strategic initiatives to raise team quality, efficiency, and value.
• Lead the AI transition to enhance workflows and impact.
• Foster cross-functional collaboration with Sustainability Advisory, Customer Success, and PM leadership.

Skills

Team management

Coaching

Customer-facing

Excel

SQL

Python

Data analysis

Communication

Tools

Excel

SQL

Python

Job description

Watershed in Mexico City is seeking a Manager for our Customer Data Services team. You will lead a seven-person Data Specialists group, drive quality and efficiency, and shape capabilities for enterprise clients.

This role focuses on coaching, operational excellence, and cross-functional collaboration to deliver high-value data services. You will own strategic initiatives, champion AI-enabled workflows, and ensure rigorous data practices while fostering an inclusive, high-performance culture in