I'm Jose Alvarez de Lugo — a Data Engineer at Moët Hennessy with a passion for building cloud, resilient data systems that scale. With over 6 years of experience and a strong foundation in cloud infrastructure, I specialize in transforming fragmented data ecosystems into reliable, automated platforms that drive real business impact.
I bring a unique blend of technical expertise and operational leadership — from orchestrating resilient data pipelines to managing cross-functional engineering workflows that keep teams aligned, unblocked, and on schedule.
Currently, I lead both technical execution and operational management:
At Moët Hennessy, I focus on data solutions that enable real-time insights and unlock operational efficiency:
- Architecting and maintaining ETL pipelines using GCP tools: Cloud Functions, Pub/Sub, Airflow, Scheduler
- Building a centralized data warehouse with BigQuery, dbt, and Terraform for Finance, Marketing, and Operations
- Managing team-wide ticketing operations: JIRA assignment, delivery tracking, and resolution support
- Implementing automated validation frameworks to improve data quality and reduce manual review
On the side, I enjoy building AI-powered tools like:
- 🤖 “AIFRED” – a GPT-powered SMS assistant (Terraform + OpenAI + Twilio) - AI Agent
- 📈 A stock analysis bot using Python, Streamlit, and value-investing principles
- 💸 Personal finance ETL system (GCP + Data Studio) for spend tracking and budgeting
- Preparing for the Google Cloud Professional Data Engineer certification
- Applying LangChain, prompt engineering, and LLM design patterns to automate workflows
- Experimenting with real-time analytics using Streamlit, Pandas, and financial APIs
I’m energized by solving problems — whether it’s through code, design, or a long photography session. My interests include:
- 📚 Reading, 📸 Photography (digital + film), ⚽ Soccer, 🏌️ Golf, ⛷️ Skiing, and ♟️ Chess
- Main Languages: Python, SQL, C
- Cloud: GCP (BigQuery, Cloud Run, Pub/Sub, Airflow, Storage), AWS (S3, EC2, Lambda)
- Infra & Pipelines: Terraform, dbt, Airflow, Cloud Scheduler
- Data Visualization: Looker Studio, Tableau, Power BI
- Extras: Shell scripting, Selenium, BeautifulSoup, Prompt Engineering, LLMs