Lindsay odyssey

I’m a Data Science graduate focused on Data Engineering, where I design ELT/ETL pipelines that move raw data into analytics-ready structures. I’m skilled in Python and SQL, and I enjoy building cloud-ready infrastructure that keeps data workflows dependable and repeatable.

In my work, I focus on orchestration, data integrity, and observability. I’ve designed real-time ingestion pipelines using Kafka and Airflow, applied dbt for Medallion-style transformations (Bronze/Silver/Gold), and optimized database structures for analytics performance—so teams can trust reporting and act faster.

I also bring a strong machine learning and deep learning foundation from my thesis work, including anomaly detection and GRU-based forecasting for financial data. On the infrastructure side, I use Docker and IaC tools like Terraform across major cloud platforms, and I’ve built monitoring with Prometheus/Grafana to support fault tolerance and zero-downtime operations.