I'm a results-oriented Data Engineer with a passion for building scalable, event-driven architectures and robust ETL pipelines. My work focuses on bridging the gap between complex data sources and actionable business insights across multi-cloud environments.
- Data Architecture: Designing high-performance Lakehouse patterns using Databricks and cloud-native services.
- Cloud-Native Ingestion: Architecting event-driven ETL processes using Python to sync external S3 data with Adobe Real-Time CDP (AEP).
- Data Modernization: Transitioning complex logic from SAS and relational DB environments into scalable Python and SQL workflows across AWS, Azure, and GCP.
I'm a tech enthusiast who believes in staying at the forefront of the data evolution:
- Cloud Mastery: Constantly researching the latest services and cost-optimization strategies within AWS, Azure, and GCP to build more resilient infrastructures.
- Modern Data Stack: Deep-diving into Databricks features (Lakehouse, Delta Live Tables) and mastering orchestration with Kafka, Airflow, Docker, and Kubernetes.
- Polyglot Programming: Exploring Java to better understand the internal mechanics of big data frameworks and distributed systems.
- Data Science Hobbyist: Leveraging the Kaggle catalog to experiment with diverse datasets, sharpening my analytical and feature engineering skills.
| Category | Tools & Technologies |
|---|---|
| Databases | AWS Redshift, PostgreSQL, Oracle, MSSQL, MySQL, Firebase |
| Data Platforms | Databricks, AWS (Glue, Athena, Lambda), Azure, GCP |
| Data Engineering | Kafka, Airflow, SAS (Base, Macro), Adobe Real-Time CDP (AEP) |
| Languages & Tools | SAS, Python, pySpark, pandas, SQL, Java, Docker, Kubernetes |
| Workflow | Linux, Crontab, Windows Server, Task Scheduler, VS Code, Git |
"Lvl. 99 Data Engineer: Mastering the art of turning coffee into automated cloud sorcery. ☕✨"