A health-data lakehouse that turns messy FHIR, claims, wearable, and notes data into three trusted outputs — analytics marts, an ML feature store, and a vector index — with de-identification, OMOP standardization, and cross-engine parity testing that caught a real de-id gap.
A live transit-data lakehouse that ingests MBTA real-time feeds, computes on-time performance, and runs, heals, and improves itself — with an agentic layer that writes its own insights and opens pull requests.
A production-grade ELT pipeline that automates daily identification of high-value customers using Apache Airflow, dbt-spark, and Apache Iceberg.
A comprehensive guide to implementing a scalable, cost-effective data pipeline and warehouse using Google BigQuery, featuring external tables, partitioning, clustering, and performance optimization with NYC taxi data.
A practical guide to building and orchestrating robust data pipelines using Apache Airflow, covering local, cloud (GCP), and Kubernetes deployments.
Workflow Orchestration using Kestra tool
A step by step guide of a simple data pipeline
An introduction to the fundamentals of data engineering