Partial Remote: GCP Data Engineer for AI Weather Pipelines

Barcelona Supercomputing Center; Barcelona; Hybrid; EUR 55,000 - 75,000; Full time

Job summary

Kyndryl, a leading technology services company, is seeking a Data Engineer to join its Applications, Data & AI Practice in Spain. You will design, build, and maintain scalable ETL/ELT pipelines on Google Cloud Platform, enabling analytics and AI use cases in enterprise environments.

The role emphasizes data quality, governance, collaboration with architects and stakeholders, and the ongoing operationalisation of data pipelines in a hybrid, flexible work setting.

Qualifications

• 3+ years of experience as a Data Engineer or similar role.
• Experience with Google Cloud Platform services: BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer, Dataproc.
• Strong SQL and Python programming skills.
• Spanish and English fluency.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines on Google Cloud Platform.
• Build and optimise 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 operationalisation of data pipelines.

Skills

SQL

Python

ETL/ELT pipelines

Data modeling

Analytics collaboration

Education

Bachelor's degree or equivalent

Tools

dbt

Spark

Kafka

Terraform

Docker

Looker

Power BI

Job description

Kyndryl, a leading technology services company, is seeking a Data Engineer to join its Applications, Data & AI Practice in Spain. You will design, build, and maintain scalable ETL/ELT pipelines on Google Cloud Platform, enabling analytics and AI use cases in enterprise environments.

The role emphasizes data quality, governance, collaboration with architects and stakeholders, and the ongoing operationalisation of data pipelines in a hybrid, flexible work setting.