Data Engineer
Data Engineer in Kyndryl's Applications, Data & AI practice in Sevilla, building and maintaining scalable ETL/ELT pipelines and cloud-native data platforms on Google Cloud (BigQuery, Dataflow, Composer) to support analytics, reporting, and AI use cases for enterprise clients. Needs 3+ years' data engineering experience, strong SQL/Python, and fluent Spanish and English.
- Compensation
- Not disclosed
- Location
- Sevilla, Spain
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 3+ years of experience as a Data Engineer or similar role
- Hands-on experience with GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer, 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
- Fluent Spanish and English
- Strong analytical thinking and attention to detail
- Collaborative and team-oriented mindset
Nice to have
- Experience with dbt, Spark, Kafka, Terraform, or Docker
- Familiarity with streaming architectures and event-driven integration patterns
- Exposure to analytics and BI tools such as Looker or Power BI
- Knowledge of AI/ML data pipelines and MLOps concepts
Full description
Who We Are
At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world’s leading businesses. We are at the heart of progress;
with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. For our people—Kyndryls—that means doing purposeful work that powers human progress. Join us and experience a flexible, supportive environment where your well-being is prioritized and your potential can thrive.
The Role
We are looking for a Data Engineer to join Kyndryl’s Applications, Data & AI (ADAI) practice, supporting the implementation of modern cloud-native data platforms on Google Cloud Platform (GCP).
The ideal candidate is passionate about building scalable and reliable data pipelines, enabling analytics and AI use cases, and delivering high-quality data solutions in enterprise environments.
Key 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.
Who You Are Required Experience:
- 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 fluid level.
Preferred Technical Skills:
- Experience with dbt, Spark, Kafka, Terraform, or Docker.
- Familiarity with streaming architectures and event-driven integration patterns.
- Exposure to analytics and BI tools such as Looker or Power BI.
- Knowledge of AI/ML data pipelines and MLOps concepts is a plus.
Soft Skills
- Strong analytical thinking and attention to detail.