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 ideal 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?