Ersi Hodo

• Led data engineering projects through development, delivering high-quality data across the organization • Pioneered data observability strategy with leadership, integrating it across data flow and analytics teams • Optimized data ecosystem using Snowflake features • Re-architected ELT pipelines for improved scalability, performance, and cost-efficiency • Influenced data platform strategy decisions on infrastructure, quality, and governance • Mentored data engineers, fostering their growth

•Owning and leading Data Engineering projects •Working closely with stakeholders and other teams to design and develop new functionalities on the system •Founder of the Engineering Blog in the company •Mentor of new employers in the Data Engineering team •Designing and developing Big Data analytics applications using PySpark/Hive/Snowflake •Optimized the ETL batch jobs run time from 24-36 hours to 1 hour •Developed the migration from HIVE to PySpark of ETL processes with the aim to save time/cost

•The aim of the project is detection of anomalies in energy distribution networks • Responsible for building anomaly based intrusion detection system by using machine learning approaches • Tools: Python (Proficient), WEKA (Proficient), C (Proficient), SQL (Proficient)

•The aim of the project was to build a third party auditing protocol for the ARCHISTAR Multi-Cloud storage • Responsible for implementation of the protocol in JAVA language • Tools: JAVA (Medium), Amazon EC2

• The aim of the project was to build a data anonymization tool that substitutes session participant information with matching but nondescript labels • Responsible for implementation of the anonymization technique in C++ • Tools: C++ (Medium), Wireshark (Proficient)