Data Engineer Medior | AWS, Snowflake, dbt & Airflow About the role We are looking for Data Engineers to join a collaborative data team within an international technology environment. In this role, you will design, develop, and maintain data pipelines, data models, ETL/ELT processes, and data integration workflows to support analytics, reporting, and data-driven decision-making. This is a hands-on Data Engineering role, focused on building reliable, scalable, and well-documented data solutions. You will work closely with Data Scientists, Data Analysts, and business stakeholders to ensure data is available, accurate, consistent, and ready to be used across different business initiatives. The adecuado profile is a Medior / Middle Data Engineer, with solid experience in Python, SQL, cloud data platforms, data warehousing, ETL/ELT, and data quality. This is not a senior leadership role, but a great opportunity for someone who enjoys technical delivery, ownership, and working in a cross-functional data team. What you’ll do Design, implement, and maintain data pipelines for ingesting, processing, and transforming data from multiple sources Build and optimise ETL/ELT workflows to ensure data availability, reliability, and freshness Clean, transform, and enrich raw data into usable formats for analytics and reporting Create and maintain data models, schemas, and data structures aligned with business needs Work with data warehousing and data integration processes Implement data quality standards and procedures to ensure data accuracy and consistency Monitor, troubleshoot, and resolve data quality and pipeline issues Contribute to data governance practices and documentation Support data security, access control, and compliance best practices Maintain clear documentation of data processes, pipelines, and data dictionaries Collaborate with Data Scientists, Analysts, and business stakeholders to understand requirements and deliver data solutions Participate in a cross-functional data environment with exposure to analytics and data science initiatives Must Have 2–5 years of experience in Data Engineering or related roles Strong hands-on experience with Python Strong proficiency with SQL Experience designing and maintaining data pipelines Good understanding of ETL/ELT processes and data integration Experience with data warehousing concepts Experience with data modelling Knowledge of data quality and data governance practices Experience with cloud-based data environments, ideally AWS Experience or exposure to tools such as Snowflake, dbt, Airflow, GitHub, Redshift, or similar Ability to write clean, maintainable, and well-documented code Strong problem-solving skills and attention to detail Good communication and teamwork skills Ability to work collaboratively in a cross-functional data team Fluent Spanish and English ✨ Nice to Have Experience with AWS-native data services Hands-on experience with Snowflake Experience with dbt for data transformation and modelling Experience with Apache Airflow or similar orchestration tools Experience with Amazon Redshift Experience with other cloud platforms such as Azure or GCP Familiarity with data security, privacy, access controls, or encryption practices Hybrid model - 2 days onsite per week Why join this project?