Data Engineer - AI Pipelines on GCP (Remote)

Sita - Société Internationale De Télécommunications; Barcelona; Hybrid; EUR 55,000 - 75,000; Full time

Job summary

Kyndryl is seeking a Data Engineer to join its ADAI practice, focusing on building scalable data platforms on Google Cloud. You will design and maintain ETL/ELT pipelines, data models, and governance across enterprise environments.

The role emphasizes collaboration with architects and stakeholders, implementing quality controls, and supporting automation to deliver analytics and AI use cases. Hybrid-friendly culture with flexible arrangements.

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 fluent levels.

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

Data warehousing

Tools

BigQuery

Cloud Storage

Dataflow

Pub/Sub

Composer

Dataproc

dbt

Spark

Kafka

Terraform

Docker

Looker

Power BI

Job description

Kyndryl is seeking a Data Engineer to join its ADAI practice, focusing on building scalable data platforms on Google Cloud. You will design and maintain ETL/ELT pipelines, data models, and governance across enterprise environments.

The role emphasizes collaboration with architects and stakeholders, implementing quality controls, and supporting automation to deliver analytics and AI use cases. Hybrid-friendly culture with flexible arrangements.