Overview¿Interesado en saber más sobre este trabajo? Desplácese hacia abajo y descubra qué habilidades, experiencia y cualificaciones académicas se necesitan.As a Data Engineer in Kyndryl’s ADAI practice, you will build scalable cloud-native data pipelines on Google Cloud Platform to power analytics and AI use cases across enterprise environments. You will collaborate with architects and business stakeholders to design data models, ensure data quality, and automate end-to-end data workflows. This role offers the chance to work on modern data platforms within a supportive, growth‑oriented culture that values belonging and continuous learning. You will contribute to impactful data initiatives that enable smarter decisions and faster innovation.Compensaciones / BeneficiosHybrid-friendly cultureBe Well programscareer development opportunitiescertifications with Microsoft, Google, and Amazoncoaching and hands-on experiencesempowerment to grow and thriveResponsabilidadesDesign, develop,



and maintain scalable ETL/ELT pipelines on Google Cloud PlatformBuild and optimize data ingestion, transformation, and processing workflows for batch and real-time dataDevelop and maintain data models supporting analytics, reporting, and AI initiativesImplement data quality validation, monitoring, and governance controlsCollaborate with architects and business stakeholders to translate requirements into technical solutionsSupport orchestration, automation, and operationalization of data pipelinesRequisitos principales3+ years of experience as a Data Engineer or similar xhfqzwm roleHands-on experience with GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer, Dataproc)Strong SQL and Python programming skillsExperience developing ETL/ELT pipelines and distributed data processing solutionsKnowledge of data warehousing concepts and dimensional modelingSpanish and English fluentStrong analytical thinkingAttention to detailCollaborative and team-oriented mindsetdbtSparkKafka

📌 Data Engineer (Tomares)
🏢 CONVOTIS Iberia
📍 Tomares