
Data Engineer
He has consistently demonstrated his ability to design and implement high-performance data processing systems that handle large-scale data efficiently.
One of Mehmet's most notable achievements is the creation of a Java-based application that identifies order items eligible for free shipping promotions. This system processes order events from Kafka, interacts with the Rise Simulate Apply service via API calls, and outputs the API responses to a separate Kafka topic, ensuring accurate and streamlined data handling.
In addition to his technical accomplishments, Mehmet is deeply passionate about the gaming industry. He is eager to expand his knowledge of gaming metrics and analytics to contribute to improving player experiences.
Created and maintained ETL pipelines using PySpark and AWS Glue.
Worked with Apache Iceberg tables in the data lakehouse.
Deployed and scheduled workflows with AWS Managed Airflow (MWAA).
Loaded fact and dimension tables from the data lakehouse into Amazon Redshift.
Assisted in documenting new tables, columns, and data transformations.
Integrated AWS Glue Docker development environment to enable efficient local development and testing of Spark jobs.

All Data Engineers who have applied to Proxify are scored from 0 to 300 on engineering excellence, one of the five parameters we evaluate. This score reflects engineering excellence only, based on interviews, take-home assignments, live coding sessions, and/or on-the-job performance reviews. The curve shows how all evaluated Data Engineers are distributed across that range, where our acceptance threshold for this parameter sits, and where Mehmet stands.

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