RESIDENT SOLUTIONS ARCHITECT Databricks Apps & AI
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Role details
Tech stack
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Job description
We are seeking two senior Resident Solutions Architects / Forward Deployed Engineers to lead hands-on Databricks implementations for enterprise customers. The strongest candidates will bring deep Databricks ecosystem expertise, proven Databricks Apps development experience, and practical AI experience on the platform.
This is a delivery-focused role for a trusted technical advisor who can design, build, deploy, and optimize production solutions.
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 by writing and reviewing code, troubleshooting complex issues, tuning Spark workloads, and improving 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 teams to manage scope, risks, dependencies, and escalations.
Translate complex technical concepts into clear recommendations, phased roadmaps, and measurable customer outcomes.
Requirements
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, with 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 certification or comparable Databricks certification., Experience scoping professional services engagements, estimating effort, and defining technical deliverables.
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