Architect and own marketing data infrastructure, including Databricks pipelines, Gold Layer tables, semantic models, and trusted analytics foundations. Lead cross-functional data initiatives, translate ambiguous business needs into scalable solutions, ensure data quality and reliability, and mentor engineers and analysts. Build, evaluate, and monitor production LLM and agent systems, automate marketing workflows with AI, and deliver high-quality Python and SQL solutions supporting Marketing, Sales, and R&D.

Build and maintain reliable data pipelines, computed tables, and scalable data models using SparkSQL and PySpark. Integrate IoT, product, customer, external, unstructured, and ML-related data into a central data lake for analytics, causal inference, model training, and dashboards. Ensure high data quality and uptime while collaborating with data science, analytics, AI/ML, and engineering teams.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.