Líder de Almacenes y Plataformas de Datos en la Nube

La Tienda Home; Granada; Hybrid; EUR 50,000 - 75,000; Full time

Job summary

Kyndryl is seeking a Data Engineer to join the ADAI practice, delivering modern cloud-native data platforms on Google Cloud Platform. You will design scalable ETL/ELT pipelines, enable analytics and AI use cases, and ensure high-quality data solutions for enterprise environments.

The role emphasizes collaboration with architects and business stakeholders, handling data quality, and enabling reliable data processing across batch and real-time workloads in a hybrid, partially remote setting.

Qualifications

• 3+ years of experience as a Data Engineer or similar role.
• Hands-on experience with Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer, and Dataproc.
• Strong SQL and Python programming skills.
• Experience developing ETL/ELT pipelines and distributed data processing solutions.
• Knowledge of data warehousing concepts and dimensional modeling.
• Spanish and English fluency.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform.
• Build and optimize data ingestion, transformation, and processing workflows for batch and real-time data.
• Develop and maintain data models supporting analytics, reporting, and AI initiatives.
• Implement data quality validation, monitoring, and governance controls.
• Collaborate with architects and business stakeholders to translate requirements into technical solutions.
• Support orchestration, automation, and operationalization of data pipelines.

Skills

SQL

Python

ETL/ELT pipelines

Data warehousing concepts

Spanish and English fluency

Tools

Google Cloud Platform (GCP)

BigQuery

Cloud Storage

Dataflow

Pub/Sub

Composer

Dataproc

Job description

Kyndryl is seeking a Data Engineer to join the ADAI practice, delivering modern cloud-native data platforms on Google Cloud Platform. You will design scalable ETL/ELT pipelines, enable analytics and AI use cases, and ensure high-quality data solutions for enterprise environments.

The role emphasizes collaboration with architects and business stakeholders, handling data quality, and enabling reliable data processing across batch and real-time workloads in a hybrid, partially remote setting.