Data Engineer: Cloud Data Pipelines on GCP

Astek

Madrid

Hybrid

EUR 60,000 - 90,000

Full time

47 hours ago
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Job summary

Kyndryl is seeking a Data Engineer to join the Applications, Data & AI (ADAI) practice in Madrid, focusing on building cloud-native data platforms on Google Cloud Platform. You will design and maintain scalable ETL/ELT pipelines and data models to support analytics and AI initiatives.

This role requires 3+ years of experience, strong SQL and Python, and hands-on GCP services like BigQuery, Dataflow, and Pub/Sub.

Qualifications

  • 3+ years of experience as a Data Engineer or similar role.
  • Hands-on 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 fluent.

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

BigQuery
SQL
Python
ETL/ELT
Data Warehousing
Spanish & English
Cloud Data Pipelines

Tools

dbt
Spark
Kafka
Terraform
Docker
GCP

Job description

Kyndryl is seeking a Data Engineer to join the Applications, Data & AI (ADAI) practice in Madrid, focusing on building cloud-native data platforms on Google Cloud Platform. You will design and maintain scalable ETL/ELT pipelines and data models to support analytics and AI initiatives.

This role requires 3+ years of experience, strong SQL and Python, and hands-on GCP services like BigQuery, Dataflow, and Pub/Sub.

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