Remote Data Engineer - ELT Pipelines & AWS Data Platform

Mentor Talent Acquisition; Portugal; Hybrid; EUR 60,000 - 90,000; Full time

Job summary

Mentor Talent Acquisition seeks a Data Engineer to design and operate scalable ELT pipelines using Python, SQL, and AWS. You will contribute to a modern data stack and focus on data quality, performance, and maintainability.

You will design, build and maintain pipelines; implement AWS workflows; collaborate with Backend/Frontend Engineers and Product to define data requirements; monitor and document data models and architecture decisions.

Qualifications

• Experience building ETL/ELT pipelines in production environments.
• Strong SQL skills and dimensional data modeling.
• Experience with AWS (Lambda, Step Functions, S3) and data workflows.
• Understanding of data quality practices and data validation.
• Experience with Git and CI/CD.

Responsibilities

• Design, build and maintain scalable ELT pipelines.
• Implement and operate data workflows using AWS (Lambda, Step Functions, S3, Batch, etc.).
• Contribute to the evolution of our Data Platform architecture (Medallion architecture).
• Ensure data quality, consistency, and reliability across pipelines.
• Optimize data transformations for performance and cost efficiency.
• Collaborate with Backend and Frontend Engineers and Product to define data requirements.
• Monitor pipelines, troubleshoot issues and improve observability.
• Document data models, transformations and architecture decisions.

Skills

Python

SQL

AWS

ELT pipelines

CI/CD

Data quality

Observability

Tools

Terraform

Docker

Git

ClickHouse/Redshift/BigQuery

Job description

Mentor Talent Acquisition seeks a Data Engineer to design and operate scalable ELT pipelines using Python, SQL, and AWS. You will contribute to a modern data stack and focus on data quality, performance, and maintainability.

You will design, build and maintain pipelines; implement AWS workflows; collaborate with Backend/Frontend Engineers and Product to define data requirements; monitor and document data models and architecture decisions.