Leads complex client data strategy engagements from discovery through delivery. Translates business goals into technical requirements and roadmaps, recommends modern data architecture, manages cross-team dependencies, governs budgets and schedules, and maintains executive client relationships. Oversees Agile delivery, risk mitigation, staffing, reporting, and account expansion. Requires broad familiarity with ingestion, warehousing, transformation, BI, AI readiness, and modern data platforms.

Designs, builds, deploys, and operates production AI/ML and LLM systems. Responsibilities include developing RAG pipelines, fine-tuning and evaluating models, managing end-to-end MLOps lifecycles, establishing monitoring and governance practices, mentoring engineers, and leading complex cross-functional client and internal initiatives.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.