Senior Ingeniero de Datos – Google Cloud, Databricks

Kyndryl

Senior Data Engineer building Google Cloud and Databricks data platforms at Kyndryl. Designing data pipelines, lakehouses, governance, and cloud infrastructure for mission-critical business systems.

Posted 9/10/2026full-timeMexico City • 🇲🇽 MexicoSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering, focusing on designing and operating data pipelines in Databricks, managing data governance, and optimizing workloads with Spark. Proficient in implementing and automating infrastructure on Google Cloud, utilizing various tools and services to enhance data management and performance.

Highest-signal resume keywords

Data EngineeringDatabricks Pipeline DesignGoogle Cloud PlatformBigQueryData Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data WarehousingData LakehousesSpark OptimizationPythonSQLETL/ELTCI/CDApache AirflowCloud FunctionsVMs

Soft Skills

CoachingCollaboration

Tools & Technologies

DatabricksUnity CatalogBigLakeDataprocCloud ComposerCloud StorageVertex AI WorkbenchColab EnterpriseGemini EnterpriseGemini API

Certifications & Qualifications

Intermediate Google CertificationAdvanced Google CertificationIntermediate Databricks CertificationAdvanced Databricks Certification

Industry Keywords

Data GovernanceCapacity ManagementPerformance ManagementBest PracticesServerless Services

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudETLGoogle Cloud PlatformPythonSparkSQLUnity

About the role

Key responsibilities & impact

Diseñar y operar canalizaciones de datos en Databricks
Administrar catálogos mediante Unity Catalog
Gestionar capacidad y rendimiento
Optimizar cargas de trabajo con Spark
Implementar gobierno de datos, seguridad y mejores prácticas operativas
Implementar y automatizar infraestructura en Google Cloud utilizando VMs, Cloud Functions, Vertex AI Workbench, Colab Enterprise, Gemini Enterprise, Gemini API, ADK y servicios serverless
Trabajar en proyectos significativos que soportan los sistemas críticos de los clientes
Desarrollar habilidades mediante certificaciones, coaching y experiencias prácticas

Requirements

What you’ll need

+5 años en Ingeniería de Datos, Data Warehousing y Data Lakehouses
+3 años de experiencia específica en Databricks, incluyendo diseño y operación de canalizaciones de datos, administración de catálogos (Unity Catalog), gestión de capacidad y rendimiento, optimización de cargas de trabajo con Spark, gobierno de datos, seguridad y mejores prácticas de operación
Experiencia avanzada en BigQuery (Capacity Management, BI Engine, BigQuery ML), BigLake, Dataproc, Apache Airflow, DAGs, Cloud Composer, Cloud Storage, Python, SQL, Spark, CDC, ETL/ELT y CI/CD
+3 años de experiencia en Google Cloud Platform
Experiencia en implementación y automatización de infraestructura utilizando VMs, Cloud Functions, Vertex AI Workbench, Colab Enterprise, Gemini Enterprise, Gemini API, ADK y servicios serverless
Ingles intermedio
Se requiere certificaciones intermedias y avanzadas en Google y Databricks
Carrera en sistemas, informática o afín

Benefits

Comp & perks

Flexible, supportive environment
Well-being prioritized
Hybrid-friendly culture
Be Well programs supporting financial, mental, physical, and social health
Personalized development goals
Continuous feedback
Certifications with Microsoft, Google, and Amazon
Coaching and hands-on experiences
Cutting-edge learning opportunities
Employee referral program