About The Position

We are looking for a high-caliber Resident Solutions Architect (RSA) to join our Professional Services team. This is a high-impact, technical role designed for a seasoned expert who can balance deep hands-on coding with strategic consulting. As an RSA, you will be embedded with our most strategic customers, acting as a "Trusted Advisor" to design, build, and deploy production-grade Big Data and AI solutions on the Databricks platform.

Requirements

  • 8+ years in Data Engineering, Analytics, or Platform roles, with at least 10+ years in technical consulting.
  • Deep expertise in Apache Spark internals and distributed processing.
  • Advanced proficiency in Python or Scala.
  • Deep experience in at least one major cloud provider (AWS, Azure, or GCP) and working knowledge of a second.
  • Proven track record of delivering at least 6-8+ end-to-end Databricks projects.
  • Strong familiarity with production deployment practices, including CI/CD and data governance frameworks (Unity Catalog).
  • Databricks Certified Data Engineering Professional (or equivalent).
  • Ability to earn trust early, empathize with customer pain points, and manage stakeholder expectations effectively.
  • Skilled at simplifying complex technical concepts for executive-level stakeholders.
  • Comfortable working across various industries and diverse cloud environments.
  • Focuses on long-term value, identifying "quick wins" while mitigating long-term architectural risks.

Responsibilities

  • Lead short-to-mid-term professional services projects, focusing on data engineering, data science, and cloud-native architectures.
  • Write production-quality code (Python, Scala), optimize distributed compute (Apache Spark) workloads, and integrate solutions across cloud ecosystems.
  • Design reference architectures and assist customers with production-level deployments, CI/CD pipelines, and MLOps.
  • Guide customers through "Build vs. Buy" decisions, highlighting the value of scalability and maintainability over technical debt.
  • Resolve high-level technical escalations and unblock customers by debugging complex performance issues or building bridge solutions for feature gaps.
  • Work closely with Product Engineering to provide real-world feedback and influence the future roadmap of the Databricks platform.
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