Data Engineer

I am a Data Engineer with experience building scalable data pipelines, data warehouses, validation systems, and enterprise analytics solutions on Google Cloud Platform.

I develop modular Python and SQL solutions for ingestion, transformation, validation, and reporting automation. My work includes Apache Airflow DAGs, Apache Beam streaming pipelines, BigQuery, Google Cloud Storage, Pub/Sub, and Microsoft SQL Server migrations.

At Searce Inc, I have delivered end-to-end data solutions for major logistics and insurance clients. I build reliable datasets, implement data quality checks, model warehouse data, and create Looker dashboards that help senior business stakeholders make informed decisions.

I am experienced in data warehousing, Medallion architecture, ETL/ELT processes, data modeling, and LookML. I focus on reducing manual effort, improving consistency and code quality, and optimizing performance for large-scale data workloads.

I also have research and frontend development experience from an international internship at Salzburg Research, where I developed Angular interfaces for a circular economy project. In addition, I have applied machine learning techniques for chemical property prediction using Python, Keras, Pandas, and NumPy.

I hold a Bachelor of Engineering in Chemical Engineering and Google Cloud and Databricks data engineering certifications. I am open to relocation and interested in opportunities where I can contribute to modern, reliable data platforms.