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# Data Engineer

- **Company:** Electronic Arts (EA)
- **Location:** Madrid, Spain
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Cloud Computing, Data Governance, Data Integration, Data Integrity, Extract Transform Load (ETL), Data Mining, Data Warehousing, Distributed Computing Environment, Python (Programming Language), NumPy, SQL Databases, Unstructured Data, Data Storage Management, Data Storage Technologies, Snowflake, Apache Spark, Gitlab, Pandas, Pyspark, Information Technology, Integration Frameworks, Data Pipelines, Amazon Redshift, Microservices
- **Published:** August 29, 2026
- **Apply:** https://www.jobleads.com/es/job/e33caf7d2d5013fccf248c254ecaaa4a0

## About the Role

* 2+ years of industry experience as a Data Engineer or in a related field.
 * Bachelor's degree in engineering, Computer Science, Maths or a related field.
 * Proficiency in Python, SQL, and Data processing frameworks (Pandas, Numpy, Spark, PySpark).
 * Experience with data pipeline orchestration tools (Apache Airflow).
 * Strong knowledge of ETL processes, and Data modelling.
 * Knowledge about Data warehousing systems (Snowflake, Big Query, Redshift).
 * Familiarity with cloud platforms (AWS, and Azure) and data storage solutions.
 * Experience with Gitlab.
 * Experience with APIs and microservices for data integration.
 * Strong analytical mindset and ability to work with large-scale datasets.
 * Excellent communication and collaboration skills, with the ability to translate data insights into business impact.

## Description

We are hiring a Data Engineer that will report to our Localization Data & AI Manager. Loc Data & AI´s mission is to support and foster the use of data from all perspectives, along with developing policies and procedures for the monitoring and active management of data in EA Localization.

This includes an understanding of data extraction, transformation, and loading (ETL) techniques., * Design, develop, optimize, and maintain scalable data pipelines to support Data Science and AI solutions.

 * Work with structured and unstructured datasets, ensuring data integrity, quality, and accessibility for AI applications.
 * Build and manage ETL/ELT pipelines to process, clean, and transform data for BI, self-service analytics, and ML/DL model training.
 * Optimize data storage and retrieval processes, leveraging cloud-based solutions (AWS, GCP, or Azure) and distributed computing frameworks (Spark).
 * Collaborate with Data scientists and ML engineers to ensure efficient deployment of AI models in production.
 * Monitor and troubleshoot data pipeline performance, implementing improvements for scalability and efficiency.
 * Maintain and improve data governance, security, and compliance standards.


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