Hey there! I'm a Data Engineer who loves turning data into insights and tools for both business analytics and research.
- Programming Languages: SQL, Python, Bash
- Databases: BigQuery, Snowflake, PostgreSQL, AWS RDS, Redshift, AWS S3, GCS, MySQL, PrestoSQL, AWS DynamoDB, SQLite.
- Data Tools: dbt, Apache Airflow, Apache Spark, AWS Glue, AWS Kinesis, Scikit-learn, NumPy, Pandas
- Visualization Tools: Seaborn, Power BI, Redash
- Cloud Platforms: AWS, GCP
- Other Technologies: Docker, Github Actions, AWS Lambda, Terraform, Jupyter Notebooks, AWS EC2, AWS SNS, AWS Step functions, NLTK, Vader, Flask, Google VM, REDCap
As a Data Engineer at Factored, I've been instrumental in:
- Building predictive analytics ETL pipelines with Databricks Lakehouse Platform.
- Automating ELT data pipelines for cancer research data management.
- Streamlining medical image repository creation through automated file upload workflows.
- Developing web applications for medical researchers to access and annotate high-resolution images.
Previously, as a Business Intelligence Analyst at Beat App, I:
- Crafted pricing proposal models to launch new services effectively.
- Optimized data sources for dashboards to enhance business reporting and monitoring.
And during my time as an Undergraduate Researcher, I:
- Conducted a bibliometric analysis on data and text mining techniques.
- Developed models to analyze the impact of socioeconomic factors on university admissions.
I'm currently pursuing an MSc in Systems Engineering and Computer Science and hold BSc degrees in Industrial and Chemical Engineering from Universidad Industrial de Santander. I've also earned several certifications, including Databricks Data Engineer Associate and AWS Certified Cloud Practitioner.
When not working spending time outside.