Data Engineering and AI-Driven Data Products for Transformative Impact

I lead the design and delivery of enterprise-scale data platforms that turn raw operational data into AI-driven products serving engineering, analytics, and business teams. I architected a streaming data platform that ingests high-volume event data through Kafka, stages it in a document store, and serves analytics from a columnar warehouse. The platform was built validation-first, so data quality is enforced at every stage rather than discovered downstream.

On this foundation, I built AI-native products that changed how the organization accesses its data. The flagship is a text-to-SQL analytics agent grounded in a governed star schema. Business users ask questions in natural language and receive validated, warehouse-executed answers. The key design decision was grounding the agent in curated schema context and retrieval rather than freeform code generation, which is what makes it trustworthy enough for non-technical users to rely on directly. Questions that previously queued behind analyst backlogs are now answered in minutes, self-serve.

I also designed a customer analytics platform built on a dimensional model with full history tracking, powering revenue, engagement, and cohort analysis from a single governed source. Alongside it, I built ML-ready feature stores and a customer segmentation system using unsupervised clustering to surface distinct behavioral personas that now inform business strategy.

Beyond delivery, I set technical direction: schema design standards, validation-first pipeline development, and reusable reliability and lineage patterns adopted beyond my own team. As a tech lead managing five engineers, I pair hands-on architecture with mentorship, deliberately growing the team's ownership of production systems rather than centralizing expertise in myself.

The result is data that once required specialist intervention becoming self-serve, trusted, and AI-accessible. Stakeholders across functions make decisions from the same governed metrics, and the schema-grounded agent approach I established has been adopted as a reusable pattern across the organization.