Leadout Capital
Data Engineer Senior
Senior Data Engineer in Mexico City who designs, builds, and optimizes scalable ETL/ELT pipelines and data models powering analytics and business insights. Core stack includes dbt, Snowflake, Informatica, and Airflow, with strong SQL and Python.
- Compensation
- Not disclosed
- Location
- Ciudad de México, Mexico
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 5–7 years of hands-on experience in data engineering or data platform development
- Strong proficiency in SQL and working knowledge of Python or another scripting language
- Experience with dbt for data transformation and Snowflake for cloud data warehousing
- Practical understanding of Informatica and Apache Airflow for data integration and orchestration
- Solid grasp of data modeling techniques (dimensional, star/snowflake schemas)
- Familiarity with CI/CD workflows, Git, and modern DevOps practices
- Knowledge of data quality frameworks and monitoring tools
- Strong problem-solving skills and attention to detail in ensuring data reliability
- Effective communicator and team player in cross-functional environments
- Passion for data-driven decision-making and improving data infrastructure
Full description
Data Engineer
DET TEAM
Mexico City
We are seeking a Data Engineer with 5–7 years of experience to design, build, and optimize scalable data pipelines and models that power analytics and business insights. You’ll work across modern data platforms and tools—such as dbt, Snowflake, Informatica, and Airflow—to ensure reliable, high-quality data for decision‑making. This role is ideal for an engineer who enjoys problem‑solving, collaboration, and continuous learning in a fast‑paced, data‑driven environment.
Key Responsibilities
- Design, build, and maintain automated ETL/ELT pipelines using tools like dbt, Snowflake, Informatica, and Airflow.
- Develop and optimize data models to support analytics, reporting, and machine learning use cases.
- Integrate data from multiple systems to create unified, high‑quality datasets.
- Ensure data accuracy, completeness, and consistency through validation and monitoring.
- Collaborate with data analysts, product managers, and business teams to translate requirements into efficient data solutions.
- Support data governance and quality initiatives, ensuring compliance with standards and best practices.
- Contribute to the continuous improvement of data engineering processes, tools, and documentation.
- Troubleshoot and resolve issues in data pipelines, optimizing for performance and scalability.
- Stay current with emerging data technologies and engineering best practices.
Desired Skills & Experience
- 5–7 years of hands‑on experience in data engineering or data platform development.
- Strong proficiency in SQL and working knowledge of Python or another scripting language.
- Experience with dbt for data transformation and Snowflake for cloud data warehousing.
- Practical understanding of Informatica and Apache Airflow for data integration and orchestration.
- Solid grasp of data modeling techniques (dimensional, star/snowflake schemas).
- Familiarity with CI/CD workflows, Git, and modern DevOps practices.
- Knowledge of data quality frameworks and monitoring tools.
- Strong problem‑solving skills and attention to detail in ensuring data reliability.
- Effective communicator and team player, able to work in cross‑functional environments.
- Passion for data‑driven decision‑making and improving data infrastructure.