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
๐ Integration with global brands and disruptive startups.
๐ Remote work/Home office.
๐ If a hybrid or on-site modality is required, you will be informed from the first interview session.
โฐ Schedule aligned with the assigned project/work cell.
๐
Monday to Friday work schedule.
๐ Birthday day off.
๐ฅ Major medical insurance (applies to Mexico).
๐ก๏ธ Life insurance (applies to Mexico).
๐ Multicultural work environments.
๐ Access to courses and certifications.
๐ค IT meetups with special guests.
๐ Virtual integration events and interest groups.
๐บ๐ธ English classes.
๐ Opportunities across our different business lines.
๐ Proudly certified as a Great Place to Work.