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Design and present scalable Databricks Lakehouse architectures, lead data engineering and ML projects, build reference architectures and demos, validate cloud integrations, and support sales through technical account planning and customer engagement.

Design and maintain robust CI/CD pipelines, manage integrations with large customer repositories, develop full-stack software, provision cloud infra with Terraform, and implement scalable data pipelines. Learn and apply PySpark, modern data architecture, and AI/agentic tools (Claude, Cursor) to automate and accelerate engineering workflows.

Work directly with clients to design, build, and deploy end-to-end production software and AI solutions. Lead solution architecture across backend, frontend, data pipelines, and ML models; develop production-grade applications; engage stakeholders from engineers to executives; and contribute reusable frameworks and best practices.

Lead end-to-end delivery of multi-team technical programs: manage roadmaps, align cross-functional teams, improve processes (Agile/SAFe), track KPIs, and mitigate risks to deliver scalable product outcomes.