Data Engineer with expertise in designing, building, and maintaining data pipelines in both IT consulting and the Logistics industry. I have developed my data engineering skills through hands-on projects on GitHub, I have the ability to work with large datasets using a variety of technologies and tools, including Spark, Airflow, AWS S3, GCS, GCC, Dataproc, and BigQuery, CI/CD pipeline using GitLab CI and GitHub Actions, Docker, Kafka, developing dashboards and visualizations using Power BI and Looker studio (Google Data Studio)."Amazon's Inventory Clothes Project"about manage big data on clod computing to improve its inventory management to reduce costs.According to the data on online clothing orders and the quantity of clothing in Amazon's warehouses, the highest sales were in April 2022. Of the 199,536 pieces of clothing in the warehouse, 54.98% have already been ordered online. Some items have only sold 8.17% and an average of 91.65% left in stock, As a result of my project, enable to reduce inventory costs by 10%.Key Skills* SQL* Python (Pandas)* Pyspark* Bash Command Platfrom* MySQL / PostgreSQL / Microsoft SQL Server / SSMS / DBeaver* Apache (Spark,Airflow)* Azure (Databricks, Database, Data Factory, Data Lake Gen 2, Synapse Analytics)* AWS (S3)* Google Cloud (GCS, GCC, Dataproc, CloudSQL, ComputeEngine, BigQuery)* Power BI (Desktop,Service) / Looker Studio(Google data studio) * GitLab CI / GitHub Actions* JDBC Sink / Debezium* Kafka* Docker