Manager, Analytics, Data Engineering

Rise; Ecatepec de Morelos; Híbrido; MXN 900.000 - 1.300.000; Jornada completa

Descripción de la vacante

Rise is seeking a Manager, Analytics, Data Engineering based in Mexico City to lead the Data Engineering team and support the broader Analytics organization. You will develop and maintain data onboarding, ingestion, cleansing, and operational processes to ensure high-quality data for audience development, BI, data science, and client analytics.

You will collaborate with U.S. and Mexico teams, manage priorities, and translate complex requirements into actionable plans, fostering a culture of

Formación

• 5+ years of experience in data engineering, analytics engineering, BI, or related technical discipline.
• Experience with large-scale customer/audience data environments.
• Experience leading technical teams and cross-functional projects.
• Experience with distributed teams across locations preferred.

Responsabilidades

• Lead ingestion, onboarding, transformation, and maintenance of first-party audience data assets.
• Oversee data cleansing, normalization, standardization, and QA processes.
• Support identity resolution and audience enrichment initiatives.
• Collaborate with BI and Data Science to enable analytics and reporting.
• Ensure scalable data pipelines and efficient data operations.

Conocimientos

Leadership

Project management

Cross-functional collaboration

Bilingual English/Spanish

Herramientas

T-SQL

PySpark

Alteryx

Snowflake

Descripción del empleo

Rise is an award-winning , full-service Media Agency of Record that is backed by data and powered by people. We create omnichannel experiences using our proprietary tech stack and advanced analytics capabilities to help solve the unique struggles brands face today. This approach, with transparency at its core , specializes in omnichannel media, commerce and retail media, advanced in-home media, as well as content and creator marketing. We offer "Risers" the opportunity to work in an ever-evolving industry that will foster learning and development, provide an innovative work environment with diverse projects and clients, career advancement paths a collaborative team environment, corporate social responsibility initiatives, an inclusive and diverse culture, plus association with a reputable media agency. We're looking for talent like you who can continue to elevate our work and culture.

Role Overview

The Manager, Analytics, Data Engineering , will lead Rise's Data Engineering team in support of the broader Media Analytics organization. Based in Mexico City and reporting to the Associate Director of Data Management (Sussex, WI), this role is responsible for developing, implementing, and maintaining data onboarding, ingestion, cleansing, and operational processes that ensure high-quality data is accessible for audience development, business intelligence, data science, research, and client analytics solutions. This individual will play a critical role in supporting Quad's audience data ecosystem, including the ingestion and management of first-party data assets, audience enrichment processes, identity resolution initiatives, match-back methodologies, and response analysis workflows. Success in this role requires exceptional bilingual communication skills, strong cross-functional collaboration, and meticulous attention to detail. As a key liaison between Data Engineering, Business Intelligence, Data Science, and Analytics teams, this leader will ensure data assets are accurate, scalable, and actionable while supporting the continued growth of Quad's audience and measurement capabilities.

Location

Location: Mexico City, 3 days in office; Applicants must hold Mexican citizenship

Leadership – People & Project Management

• Build, lead, and develop the Data Engineering team in Mexico City, fostering a culture of accountability, collaboration, innovation, and continuous improvement.
• Manage project priorities, resource allocation, and delivery timelines across multiple concurrent initiatives supporting broader data engineering projects managed from Sussex.

Audience Data Management

• Lead the ingestion, onboarding, transformation, and maintenance of first-party audience data assets across Quad's data ecosystem.
• Oversee data cleansing, normalization, standardization, and quality assurance processes to ensure data accuracy and usability using existing infrastructure, schemas, and tools.
• Support identity resolution and audience enrichment initiatives through scalable data engineering practices.
• Collaborate with the U.S.-based team to improve and maintain automated workflows supporting audience creation, audience activation, and measurement processes.

Match-Back & Response Analysis Enablement

• Facilitate data preparation and engineering processes required for match-back analysis, attribution measurement, and response analysis initiatives.
• Partner closely with Business Intelligence and Data Science teams to ensure data assets are structured and accessible for analytical modeling and reporting.
• Support the development of scalable processes that improve campaign measurement accuracy and operational efficiency.

Cross-Functional Collaboration

• Work closely with Business Intelligence, Data Science, Analytics, Client Services, Product, and Technology teams to support data-driven decision-making.
• Collaborate with U.S.- and Mexico-based stakeholders to gather requirements, prioritize initiatives, and deliver high-quality data assets.

Communication & Stakeholder Management

• Act as a bridge between U.S.-based and Mexico City-based technical and non-technical team members, translating complex requirements into actionable project plans.
• Lead meetings, project discussions, and presentations in both English and Spanish.
• Communicate project status, risks, dependencies, and recommendations clearly to leadership and business partners.

Data Operations & Performance Optimization

• Ensure Business Intelligence and Data Science teams have timely access to clean, reliable, and well-documented data.
• Monitor and optimize data pipelines, automation processes, and platform performance.
• Identify opportunities to improve operational efficiency, reduce manual effort, and enhance data quality across the analytics ecosystem.

Qualifications & Experience

• 5+ years of experience in data engineering, analytics engineering, business intelligence, or a related technical discipline.
• Experience working with large-scale customer, audience, marketing, or first-party data environments.
• Experience supporting audience development, identity resolution, match-back analysis, campaign measurement, or response analytics initiatives preferred.
• Experience leading technical teams and managing cross-functional projects.
• Experience working with distributed teams across multiple geographic locations preferred.
• Media, marketing, advertising, customer analytics, or audience analytics experience strongly preferred.

Knowledge, Skills & Abilities

Language Skills

• Fluent bilingual proficiency in English and Spanish required.
• Ability to communicate effectively with business and technical stakeholders in both languages.
• Ability to lead meetings, create documentation, present findings, and collaborate daily in English and Spanish.

Communication & Collaboration

• Exceptional written and verbal communication skills.
• Strong collaboration and relationship-building skills across diverse teams and functions.
• Ability to work effectively in a highly collaborative environment with stakeholders in both Mexico and the United States.

Attention to Detail

• Exceptional attention to detail and commitment to data accuracy, process consistency, and operational excellence.
• Ability to identify data quality issues, troubleshoot root causes, and implement sustainable solutions.

Technical Skills

• T-SQL
• PySpark
• Alteryx
• Snowflake

Leadership Skills

• Proven ability to build, develop, and retain high-performing technical teams.
• Strong project management, prioritization, and organizational skills.
• Ability to balance tactical execution with continuous process improvement.

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