Databricks Solution Architect

Job Title: Databricks Solution Architect with AI

Location: Remote

Experience: 17+ Years

Key Responsibilities:

• Lead customer-facing Databricks engagements from discovery and architecture through production deployment and adoption.
• Design and develop Databricks Apps and production-grade data/AI solutions using Python or Scala, SQL, Apache Spark, Delta Lake, and Databricks platform services.
• Build reference architectures and scalable solutions across batch/streaming data engineering, analytics, AI/ML, and GenAI use cases.
• Own technical delivery: write and review code, troubleshoot complex issues, tune Spark workloads, and improve performance, reliability, and cost.
• Implement CI/CD, MLOps, security, governance, observability, and operational best practices for enterprise deployments.
• Partner with customer stakeholders, project managers, account teams, engineering, and support to manage scope, risks, dependencies, and escalations.
• Translate complex technical concepts into clear recommendations, phased roadmaps, and measurable customer outcomes.

Required Qualifications:

• 17+ years of overall IT experience, including senior architecture, engineering, consulting, or platform delivery responsibilities.
• 5+ years of recent, hands-on experience across the Databricks ecosystem; demonstrated delivery of multiple production implementations.
• Strong Databricks Apps development experience, including secure application architecture, data access, deployment, and lifecycle management.
• Deep expertise in Apache Spark and distributed computing, including runtime behavior, optimization, scalability, and production troubleshooting.
• Advanced coding skills in Python and/or Scala plus strong SQL and data architecture fundamentals.
• Deep expertise in at least one cloud platform (AWS, Azure, or Google Cloud Platform) and working knowledge of a second.
• Proven consulting and executive-facing communication skills, with the ability to build trust and guide technical decisions.

Highly Preferred:

• Hands-on AI/ML or GenAI experience on Databricks, including MLflow/Mosaic AI, model serving, vector search, RAG, agents, or production MLOps.
• Databricks Data Engineer Professional or comparable Databricks certification.
• Experience scoping professional services engagements, estimating effort, and defining technical deliverables.