Data Architect – Databricks & GenAI

Key Responsibilities:

• Design and develop reusable Databricks frameworks for process orchestration, integration, validation, governance, and deployment
• Build standardized orchestration patterns — multi-task workflows, dependency chains, retries, checkpointing, and audit logging
• Develop CI/CD-ready project scaffolding with validation, testing, policy checks, and environment promotion patterns
• Build reusable GenAI application frameworks — RAG pipelines, prompt/version management, telemetry, and guardrails
• Build agentic app frameworks supporting multi-step execution with enterprise integrations and safety controls
• Rapidly deliver POCs (days, not weeks) and convert them into reusable accelerators and reference implementations
• Conduct technology assessments across integration, orchestration, AI/BI tooling, governance, and observability
• Produce high-quality documentation — architecture guides, onboarding checklists, cookbooks, and training material

Required Skills:

• Strong hands-on Databricks experience (process orchestration, Delta Lake, Unity Catalog)
• Python + SQL — full stack strength including backend API/service development
• CI/CD pipeline experience for Databricks (GitHub Actions, Azure DevOps, or similar)
• Experience building reusable frameworks, accelerators, or templates
• GenAI/agentic app development — RAG, LLMs, tool-using agents, multi-step workflows
• Application and data security design and setup
• Ability to execute quick POCs and document findings clearly

Good to Have:

• Experience with LangChain, LlamaIndex, or similar orchestration frameworks
• Familiarity with AI/BI tooling and observability platforms
• Strong documentation and enablement skills

Ideal Candidate:

• 8+ years in data engineering or architecture
• Has built platforms/frameworks used by multiple teams
• Comfortable working across architecture, engineering, and product stakeholders
• Startup-like execution speed with enterprise-grade thinking