Data Engineer

• Design, implement, and manage ETL/ELT pipelines and data workflows.
  

• Develop scalable data models and data warehousing solutions (e.g., Redshift, BigQuery, Snowflake).
  

• Optimize performance of storage and retrieval systems (SQL, NoSQL, columnar DBs).
  

• Collaborate with backend and analytics teams to deliver reliable, structured data.
  

• Ensure data quality through validation frameworks and monitoring systems.
  

• Maintain documentation of pipelines, schemas, and data standards
  

• Contribute to decisions around data architecture, tools, and governance.

Must-have

• +5 years of experience in data engineering or backend roles with a data focus.
  

• Strong SQL skills and experience with data modeling and transformation.
  

• Proficiency in Python or similar language for data manipulation.
  

• Familiarity with cloud services (AWS/GCP) and orchestration tools (Airflow, Prefect).
  

• Experience with data pipeline tools (dbt, Kafka, Spark, etc.).
  

• Fluent in Spanish. English is a plus.
  

Nice-to-have

• Exposure to machine learning or AI-driven platforms.
  

• Experience integrating multiple data sources (APIs, webhooks, logs, external DBs).
  

• Familiarity with CI/CD, Docker, and IaC tools (Terraform).
  

• Knowledge of data privacy, security, and compliance best practices.

• Fully remote work with real autonomy and global collaboration.
  

• Paid time off, birthday leave, and personal days.
  

• Continuous learning: English classes, internal workshops, and training discounts.
  

• Holistic well-being: psychological support, wellness activities, and access to 2,500+ lifestyle benefits.