Senior Solution Architect

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

Required Skills & Experience: 8+ years in Data Engineering, Analytics, or Platform roles, with at least 10+ years in technical consulting. Technical Mastery: Deep expertise in Apache Spark internals and distributed processing. Coding: Advanced proficiency in Python or Scala. Cloud Expertise: Deep experience in at least one major cloud provider (AWS, Azure, or GCP) and working knowledge of a second. Project History: Proven track record of delivering at least 6-8+ end-to-end Databricks projects. DevOps/MLOps: Strong familiarity with production deployment practices, including CI/CD and data governance frameworks (Unity Catalog).