GCP Data Engineer — Scalable ETL/AI Pipelines (Hybrid)

Ntt Data Europe & Latam; Barcelona; Hybrid; EUR 60,000 - 90,000; Full time

Benefits offered by this job

Be Well programs

Hybrid-friendly culture

Job summary

Kyndryl is seeking a Data Engineer to join its ADAI practice, focusing on cloud-native data platforms on Google Cloud Platform. You will design scalable ETL/ELT pipelines, ingest and transform data for analytics and AI use cases, and ensure data quality and governance in enterprise environments.

Ideal candidates have 3+ years of experience, strong SQL/Python skills, and familiarity with tools like dbt, Spark, Kafka, Terraform, and Docker, with bilingual Spanish/English proficiency.

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.

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

GCP

SQL

Python

Data modeling

ETL/ELT pipelines

Distributed processing

Spanish & English

Tools

dbt

Spark

Kafka

Terraform

Docker

Looker

Power BI

Job description

Kyndryl is seeking a Data Engineer to join its ADAI practice, focusing on cloud-native data platforms on Google Cloud Platform. You will design scalable ETL/ELT pipelines, ingest and transform data for analytics and AI use cases, and ensure data quality and governance in enterprise environments.

Ideal candidates have 3+ years of experience, strong SQL/Python skills, and familiarity with tools like dbt, Spark, Kafka, Terraform, and Docker, with bilingual Spanish/English proficiency.