Senior Data Engineer - Architect Scalable Pipelines

Leadout Capital; Ciudad de México; On-site; MXN 900,000 - 1,200,000; Full time

Job summary

Leadout Capital is seeking a Data Engineer in Mexico City to design, build, and optimize scalable data pipelines and models powering analytics and insights. You will work across modern platforms such as dbt, Snowflake, Informatica, and Airflow to ensure reliable data for decision-making, in a fast-paced, data-driven environment.

The role requires 5–7 years of hands-on data engineering experience, strong SQL, and scripting skills (Python or similar).

Qualifications

• 5–7 years of hands-on data engineering experience.
• Strong SQL and scripting skills (Python or similar).
• Experience with dbt, Snowflake, Informatica, and Airflow.
• Solid understanding of data modeling (dimensional, star/snowflake).

Responsibilities

• Design, build, and maintain ETL/ELT pipelines across tools (dbt, Snowflake, Informatica, Airflow).
• Develop and optimize data models for analytics, reporting, and ML use cases.
• Integrate data from multiple systems to create unified datasets.
• Ensure data accuracy, completeness, and quality through validation and monitoring.
• Collaborate with analysts, product managers, and business teams to translate requirements into data solutions.
• Support data governance and quality initiatives and adhere to standards.
• Contribute to improving data engineering processes, tooling, and documentation.
• Troubleshoot and resolve data pipeline issues to optimize performance and scalability.
• Stay updated with emerging data technologies and best practices.

Skills

SQL

Python

Cross-functional collaboration

Attention to detail

Problem-solving

Tools

dbt

Snowflake

Informatica

Apache Airflow

Git

Job description

Leadout Capital is seeking a Data Engineer in Mexico City to design, build, and optimize scalable data pipelines and models powering analytics and insights. You will work across modern platforms such as dbt, Snowflake, Informatica, and Airflow to ensure reliable data for decision-making, in a fast-paced, data-driven environment.

The role requires 5–7 years of hands-on data engineering experience, strong SQL, and scripting skills (Python or similar).