Databricks Architect/ Solution Architect

Key Responsibilities: Lead short-to-medium-term professional services projects focused on data engineering, data science, and cloud-native architectures. Write production-quality code using Python and Scala. Optimize distributed computing workloads using Apache Spark. Integrate data 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, emphasizing scalability and maintainability while minimizing technical debt. Resolve high-level technical escalations and unblock customers by debugging complex performance issues or developing bridge solutions for feature gaps. Collaborate with Product Engineering to provide real-world feedback and contribute to the future roadmap of the Databricks platform. Build and deploy production-ready solutions while addressing complex data engineering challenges. Guide customers in adopting a Data and AI-driven approach to business transformation.

Required Qualifications: 15+ years of experience in Data Engineering, Analytics, or Platform roles.10+ years of experience in technical consulting. Deep expertise in Apache Spark internals and distributed processing. Advanced proficiency in Python or Scala. Deep experience with at least one major cloud provider (AWS, Azure, or GCP) and working knowledge of a second cloud platform. 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 such as Unity Catalog. Databricks Certified Data Engineering Professional certification or equivalent.

Preferred Qualifications: Ability to build customer trust, understand customer pain points, and manage stakeholder expectations effectively. Strong communication skills, including the ability to simplify complex technical concepts for executive-level stakeholders. Adaptability to work across various industries and diverse cloud environments. Strategic thinking with the ability to identify quick wins while mitigating long-term architectural risks. Ability to balance strategic architecture with hands-on engineering, implementation, and technical troubleshooting.