Data Architect (Gcp)

OverviewAs a Data Architect at Kyndryl, you will define and govern scalable data ecosystems on Google Cloud Platform to support enterprise data transformations.You’ll translate business needs into architectural roadmaps and lead delivery teams to implement data platforms.Your work enables secure, compliant, data-driven decisions across the organization.This role offers meaningful impact in shaping modern data architectures within a collaborative, growth-oriented culture.Compensaciones / Beneficioshybrid-friendly cultureBe Well programs (financial, mental, physical, social health)continuous learning opportunitiescertifications with Microsoft, Google, Amazoncoaching and hands-on experiencescareer development tools and feedback mechanismsResponsabilidadesDesign and define enterprise-scale data architectures on Google Cloud Platform (GCP)Translate business and technical requirements into scalable data platform strategies and roadmapsDesign data ecosystems including data lakes, data warehouses, lakehouse patterns, and real-time processingLead and mentor data engineering teams during implementation and delivery phasesEnsure solutions meet enterprise security, governance, and data quality standardsCollaborate with technical and non-technical stakeholders to align architecture with business objectivesRequisitos principales5+ years designing and implementing enterprise data platforms and architecturesStrong experience with GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Composer, Vertex AI)Expertise in data lakes, data warehouses, and lakehouse patternsExperience leading technical teams and coordinating implementation activitiesSolid understanding of ETL/ELT, orchestration, and data integration patternsAnalytical mindsetStructured problem-solvingStakeholder collaborationdbtAirflowSpark

Strong experience with GCP services (BigQuery, Cloud Storage, Dataflow, Pub/Sub, Dataproc, Composer, Vertex AI) Expertise in data lakes, data warehouses, and lakehouse patterns Experience leading technical teams and coordinating implementation activities Solid understanding of ETL/ELT, orchestration, and data integration patterns Analytical mindset Structured problem-solving Stakeholder collaboration dbt Airflow Spark