Building reliable ETL pipelines on Google Cloud. Turning raw, messy data into clean, queryable assets that teams can trust.
Data Engineer working remotely on production ETL pipelines, currently finishing a B.Sc. in Data Science. I design ingestion and transformation workflows that move data from heterogeneous sources into BigQuery, model it for analytics, and surface it through clean dashboards. I care about readable code, reproducible environments, and pipelines that fail loudly instead of silently.
- Designing and maintaining ETL pipelines on GCP / BigQuery
- Writing Python and SQL for data ingestion, transformation, and modeling
- Building analytics layers and dashboards for decision-making
- Comfortable across the full path: raw source to trusted table
Languages
Data & Cloud
Python Ecosystem
Tooling
Dynamic Pricing Engine — Reinforcement Learning A pricing agent that learns to set prices in a simulated marketplace. Demand is modeled from real retail data, competitor prices are pulled live via API, and a PPO agent is trained against a custom Gymnasium environment. Includes a Streamlit dashboard with a Human-in-the-Loop mode for supervised decisions.
Python · Stable-Baselines3 · Gymnasium · scikit-learn · Streamlit