Top Data Engineer Jobs in Mexico

The Senior Data Platform Engineer leads the design and management of enterprise data pipelines using Python and AWS. Responsibilities include building APIs, deploying services, and designing ETL pipelines to support finance-related analytics and systems.

As a Senior Data Engineer, you will design, build, and maintain scalable data platforms, ETL pipelines, and support analytics and ML workflows, ensuring data quality and cross-functional collaboration.

The Senior Data Engineer will design, implement, and optimize data platforms, ensuring performance and quality in an agile environment.

Responsible for developing and supporting data platform infrastructure, collaborating with teams to provide data solutions and mentoring junior engineers.

Responsible for integrating data across MSP tools, ensuring real-time accuracy, consulting on customer needs, and developing BI reports and RPA solutions.

The Machine Learning Engineer / Data Scientist will build and deploy machine learning solutions, translating business needs into ML problems, working with data analysis, model development, and productionization tasks.

Design, build, and optimize scalable data pipelines using PySpark, integrating data from multiple sources into a centralized data warehouse. Collaborate with teams to ensure data quality and develop analytics solutions.

As a Senior Data Engineer, you'll manage end-to-end data processes, create and maintain data pipelines, and develop ETL/ELT processes while collaborating with BI teams and extracting insights from large datasets.

As a Software Engineer, you'll design, build, and maintain data platform products, ensuring operational excellence and high availability while collaborating with internal teams and contributing to open-source tools.

The Senior Data Engineer + AI will design and optimize data architectures, develop data pipelines, integrate AI models, and mentor junior engineers while ensuring data governance and collaboration with data scientists.

The Senior Data Engineer will lead the development and maintenance of data pipelines, ensuring data governance and performance in a collaborative Agile environment.

Drive quality assurance strategy for data migration projects, validating data integrity and automation using AWS technologies and Python scripts.

The Senior Data Engineer will design and build scalable data pipelines in Snowflake and dbt, optimize performance, and lead technical efforts while mentoring the team.

As a Staff Engineer in Data Science, you will leverage your coding skills to tackle client challenges, guide teammates, and enhance solutions for greater success.

The Staff Engineer, Data Science role focuses on leveraging tech skills to enhance team capabilities and provide advanced solutions for client challenges.

Design, build, and maintain scalable Airflow-based data pipelines and reusable components. Implement CI/CD for deployments, enforce data governance and quality, monitor and troubleshoot workflows, document solutions, and mentor teammates on Airflow best practices.

The Senior Data Engineer will design and maintain data pipelines, mentor engineers, and implement data governance while using tools like Snowflake and dbt.

As a Senior Data Engineer, you will develop SQL queries, analyze data structures in Snowflake, and ensure data availability within an Agile framework while participating in technical discussions and data quality reviews.

The Principal Engineer will oversee data infrastructure, optimizing databases, and facilitating data systems for high volume processing while integrating new technologies.

Lead the migration of SQL Server and PostgreSQL to Azure SQL. Design and support PaaS and DBaaS offerings while optimizing database instances.

The Senior Data Engineer will enhance data-driven applications and platforms, focusing on data integration, optimizing warehouses, and ensuring data quality, collaborating with various teams for implementation.

As a Senior Data Engineer, you'll design, build, and maintain cloud-native data pipelines and architectures for analytics and machine learning workloads, collaborating with cross-functional teams.