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Salary
≈ $47k – $112k per year (Estimated)
Location
In office (Heredia)
Seniority
Architect

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Sep 28, 2026. IBM scores A on the Alion truth index.

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IBM

IBM is an American technology company whose roots go back to the 1911 formation of the Computing-Tabulating-Recording Company, and which has been headquartered in Armonk, New York for decades. It defined mainframe computing, the personal computer standard and much of enterprise data processing, and today concentrates on hybrid cloud built around Red Hat, enterprise AI through the watsonx platform, consulting services and the mainframe and storage systems that still run the world's largest transaction workloads. The company also runs one of the leading quantum computing programmes and consistently ranks among the largest recipients of United States patents.

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As a Solution Architect specializing in Data Platforms, you design end-to-end Big Data Solutions across various platforms and manage large data repositories. You leverage expertise in industry standards, best practices, and leading technologies to create tailored data solutions for clients. Your primary responsibilities will include:

  • Design End-to-End Solutions: Design comprehensive Big Data Solutions across multiple platforms, incorporating industry standards and best practices to meet client needs.
  • Oversee Data Platform Architecture: Lead the development of architectures for data platform and cognitive components, including unstructured data technologies, annotation, and related data and analytics.
  • Manage Large Data Repositories: Manage and maintain large data repositories, ensuring scalability and performance, and leveraging expertise in HADOOP Framework, Ecosystem, MapReduce, and Data on Containers.
  • Develop Cloud-Based Solutions: Create data solutions using Cloud-native platforms such as AWS, Azure, Google, IBM Cloud, or Cloud-Native data platforms like Snowflake, tailored to client requirements.
  • Deliver Client-Facing Solutions: Collaborate with clients to understand their needs and deliver customized data solutions that meet their business objectives.
  • Cloud-Native Architecture Design: Proven experience designing and overseeing cloud-native data platform architectures, with a focus on Snowflake, Databricks, or similar modern data stack platforms
  • Medallion Architecture Implementation: Hands-on experience implementing medallion architecture, including semantic layers
  • Scalability & Elasticity: Proficiency in managing auto-scaling, cluster configuration, and resource optimization in serverless/cloud-native architectures
  • Scalable Data Pipelines: Experience architecting auto-scaling, serverless data pipelines and ETL/ELT processes using cloud-native technologies
  • Industry Best Practices: Knowledge of best practices, including separation of compute and storage, query optimization, and cost efficiency
  • Data Repository Management: Hands-on experience managing large-scale data repositories with CI/CD practices
  • Snowflake Specialization: Advanced expertise in Snowflake architecture, including multi-cluster deployments, role-based access control (RBAC), Snowflake SQL, and Snowflake Native Apps; OR Databricks Specialization: Advanced expertise in Databricks platform, including Delta Lake, Unity Catalog, Apache Spark, collaborative notebooks, and MLflow integration
  • Primary Cloud Providers: Demonstrated experience on Azure (ADLS Gen2, Synapse, Data Factory)
  • Modern Data Stack Integration: Experience integrating Snowflake/Databricks with modern tools (dbt, Fivetran, Informatica, Apache Airflow, Prefect, Dagster).
  • AI Foundational Concepts: Familiarity with foundational AI/ML concepts and experience with Snowflake Cortex or similar embedded AI capabilities; understanding of how AI components integrate into data platforms and basic knowledge of LLM applications
  • Snowflake or Databricks Certification Costa Rica Infrastructure & Technology Hybrid Professional Heredia, CR (0804) IBM Business Transformation Center, S.r.l.
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