Data Engineer: Build Scalable Pipelines & SSOT Data Assets

Amazon.com; Madrid; On-site; EUR 55,000 - 85,000; Full time

Job summary

Amazon.com in Madrid is seeking a skilled Data Engineer to design and maintain scalable data pipelines, models, and curated datasets that support strategic decision-making across the logistics network.

You will collaborate with cross-functional teams to translate business needs into robust data solutions, monitor data quality, and drive future data storage and integration initiatives, in a fast-paced environment.

Qualifications

• Experience in data engineering.
• Experience with data modeling, warehousing and building ETL pipelines.
• Proficiency with SQL, Python, and data processing languages.
• Familiarity with cloud data services and big data tools preferred.

Responsibilities

• Design, implement, and automate scalable data pipelines for collecting, transforming, and processing data from multiple sources (Redshift, Glue).
• Design and evolve data models and schemas ensuring accuracy, consistency, and alignment with single source of truth standards.
• Own the development and maintenance of curated reference datasets and data assets to drive key business decisions.
• Monitor and troubleshoot data quality issues and operational incidents in production pipelines.
• Drive architectural plans and implementation for future data storage and integration solutions.
• Collaborate with stakeholders across operations, finance, and science to translate business requirements into reliable data solutions.
• Investigate and resolve root causes of data defects, ensuring data accuracy and reliability across the platform.

Skills

Data engineering

ETL pipelines

Data modeling

SQL

Python

SparkSQL/HiveQL

Tools

AWS

Informatica

ODI

SSIS

Datastage

Job description

Amazon.com in Madrid is seeking a skilled Data Engineer to design and maintain scalable data pipelines, models, and curated datasets that support strategic decision-making across the logistics network.

You will collaborate with cross-functional teams to translate business needs into robust data solutions, monitor data quality, and drive future data storage and integration initiatives, in a fast-paced environment.