Kirtana Nambiar

Data Engineer @Double Line, Inc

NC, US

Designed and built an end-to-end Agentic AI POC leveraging LLMs, RAG, semantic similarity, and vector embeddings to automate source-to-target data mapping, reducing manual mapping effort by an estimated 60% and accelerating onboarding of new data sourcesDesigned and implemented production ELT pipelines using Medallion architecture and Kimball dimensional modeling, integrating data from multiple heterogeneous sources into a canonical schema and curated data warehouse layer supporting enterprise analytics and reportingBuilt modular, analytics engineering data models using SQLMesh (dbt-style) to enforce data contracts, improve governance, and enable self-service analytics across business teamsEngineered timestamp-based incremental ELT pipelines using stored procedures and MERGE logic, ensuring idempotency and late-arriving data handling reducing data scan volumes and optimizing resource utilization by 60% in a large-scale data warehouseEstablished a data quality and governance framework covering automated testing, audit logging, lineage tracking, and RBAC-based access controls, achieving CEDS compliance and measurably improving data reliability and client satisfactionLeveraged AI-assisted development (Cursor, LLM code generation) to accelerate pipeline development, query optimization, and debugging cyclesArchitected end-to-end ETL workflows and authored supporting technical documentation including data flow diagrams, runbooks, and data dictionaries to standardize engineering practices and enable cross-team knowledge transferPartnered with data stewards, business stakeholders, and product teams to translate ambiguous requirements into scalable, production-grade data solutions

George Mason University

Master's degree, Data Analytics Engineering

University of Mumbai

Bachelor’s Degree, Information Technology