Embed with client teams to map business processes and transform them into production-grade agentic AI workflows. Build LLM agents, integrations, retrieval systems, evaluations, guardrails, observability, and human-in-the-loop processes using Python and agent frameworks. Facilitate stakeholder sessions, explain technical tradeoffs, document solutions, and hand off maintainable workflows. Bring reusable engineering patterns back to the consultancy.

Lead client-facing analytics engagements: translate ambiguous business questions into data models, dashboards, and KPIs; write production-quality SQL and dbt models; build BI reporting; apply AI tools to accelerate analysis; drive proactive insights; set stakeholder cadence; and mentor junior analysts to ensure adoption and delivery.

Lead Databricks pre-sales discovery and design Lakehouse architectures, author proposal technical content, run proofs-of-concept, and act as lead architect on major engagements. Own the Databricks partner relationship and co-sell motion, drive certification and internal enablement, resolve performance and governance challenges, and ensure successful production handoffs while building partner-sourced pipeline and scaling the Databricks practice.