About The Position

As a Principal Solutions Architect, you'll be a senior technical leader who designs large-scale data platforms. You'll partner with engineering, product, and business teams to set technical direction for complex, high-volume data systems. You'll have opportunity to: Define end-to-end architecture for large-scale data platforms and distributed systems Develop automated, custom data pipelines using Apache Spark, Trino, or similar Big Data technologies Establish architecture best practices for data ingestion, transformation, storage, and usage Improve performance, scalability, resiliency, and cost efficiency across data platforms Partner with Product, Engineering, Security, Cloud, and Architecture teams to modernize legacy workflows and translate our needs into technical solutions Lead architecture reviews, resolve cross-team technical decisions, and define practices for data governance, security, and observability Mentor architects and engineers, and communicate technical strategy and risk to senior leadership

Requirements

  • Bachelor's in Computer Science, Data Engineering, or related field, or equivalent experience (Master's preferred)
  • 8+ years of experience in software engineering, data engineering, or technology architecture
  • 5+ years of hands-on experience with Big Data technologies and large-scale distributed data processing
  • Experience designing and building automated, custom data pipelines using Apache Spark, Trino, or similar frameworks
  • Experience architecting enterprise-scale data platforms and distributed systems
  • Experience designing solutions in cloud environments and with expertise in Python, Java, Scala, or SQL
  • Experience with data lakes, data warehouses, object storage, and distributed query engines
  • Reside in, or near the designated Collaboration Hub(s) for this role.

Responsibilities

  • Define end-to-end architecture for large-scale data platforms and distributed systems
  • Develop automated, custom data pipelines using Apache Spark, Trino, or similar Big Data technologies
  • Establish architecture best practices for data ingestion, transformation, storage, and usage
  • Improve performance, scalability, resiliency, and cost efficiency across data platforms
  • Partner with Product, Engineering, Security, Cloud, and Architecture teams to modernize legacy workflows and translate our needs into technical solutions
  • Lead architecture reviews, resolve cross-team technical decisions, and define practices for data governance, security, and observability
  • Mentor architects and engineers, and communicate technical strategy and risk to senior leadership
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