Principal Data Engineer

Role Overview

• Lead the design, development, and optimization of modern data platforms that enable advanced analytics, machine learning initiatives, and data-driven decision-making.
• Work closely with Data Scientists, Analysts, Product teams, and business stakeholders to transform complex data ecosystems into reliable, scalable, and secure platforms that generate meaningful business insights.
• Design, build, and maintain large-scale data platforms and data architectures.
• Lead the development of scalable and reliable ETL/ELT pipelines for batch and near real-time processing.
• Architect cloud-native data solutions leveraging AWS, Azure, or GCP services.
• Drive data modeling strategies using methodologies such as Star Schema, Snowflake Schema, and Data Vault.
• Define and enforce data engineering best practices, coding standards, governance policies, and architectural guidelines.
• Implement orchestration frameworks using tools such as Airflow, dbt, or similar technologies.
• Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
• Collaborate with Data Scientists and Analytics teams to ensure high-quality, production-ready datasets.
• Establish monitoring, observability, testing, and data quality frameworks.
• Lead technical discussions and architectural decisions across multiple teams.
• Conduct code reviews and mentor Data Engineers across different seniority levels.
• Implement data security, privacy, and compliance standards aligned with industry best practices.
• Support strategic initiatives involving analytics, machine learning, and marketing intelligence platforms.

Requirements

• 8+ years of experience in Data Engineering, Data Platforms, or Data Architecture roles.
• Experience operating in Senior, Lead, Staff, or Principal Data Engineering positions.
• Proven track record designing and implementing enterprise-scale data solutions.
• Experience working in distributed and cloud-native environments.
• Expert-level SQL skills.
• Strong Python development experience for data engineering and processing.
• Extensive experience building ETL/ELT pipelines.
• Hands-on experience with Airflow, dbt, or equivalent orchestration tools.
• Strong expertise in data modeling and warehouse design.
• Experience with modern cloud platforms:
• AWS
• Azure
• GCP
• Experience with data lakes and data warehouses.
• Knowledge of CI/CD practices for data platforms.
• Understanding of data governance, security, lineage, and privacy controls.
• Familiarity with analytics and machine learning data preparation workflows.
• Strong ownership mentality.
• Excellent communication and stakeholder management skills.
• Ability to lead technical initiatives and influence engineering decisions.
• Mentoring and coaching capabilities.
• Strategic problem-solving mindset.
• Adaptability in fast-paced environments.
• Strong collaboration skills across technical and business teams.
• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Data Science, or related field.
• Advanced English (required).

Tech Stack

• Airflow
• AWS
• Azure
• Cloud
• ETL
• Google Cloud Platform
• Python
• SQL
• Vault

Benefits

🌎 Integration with global brands and disruptive startups. 🏠 Remote work/Home office. 📍 If a hybrid or on-site modality is required, you will be informed from the first interview session. ⏰ Schedule aligned with the assigned project/work cell. 📅 Monday to Friday work schedule. 🎂 Birthday day off. 🏥 Major medical insurance (applies to Mexico). 🛡️ Life insurance (applies to Mexico). 🌍 Multicultural work environments. 📚 Access to courses and certifications. 🎤 IT meetups with special guests. 🎉 Virtual integration events and interest groups. 🇺🇸 English classes. 🚀 Opportunities across our different business lines. 🏆 Proudly certified as a Great Place to Work.