Adam Klibi

- Engineered and automated ETL pipelines in Informatica Cloud and dbt, integrating data from SAP, Salesforce, and AWS S3 into Snowflake, cutting processing time by 30%. - Optimized Airflow orchestration to enhance task parallelism and reduce job failures by 60%. - Designed modular dbt models improving maintainability, data lineage visibility, and performance by 40%. - Built analytical data marts enabling Power BI dashboards with incremental refresh, reducing query latency by 30%. - Collaborated cross-functionally to standardize data quality frameworks and enforce governance best practices in Azure and Snowflake environments.

- Built and optimized cloud-native data infrastructure and CI/CD pipelines to support real-time data processing and analytics. - Developed a real-time data streaming pipeline in Rust and Kafka, improving data throughput and reliability by 50%. - Reduced Docker build times by 40% through multi-stage builds and efficient caching strategies. - Enhanced CI/CD workflows with GitHub Actions, accelerating deployment cycles and improving pipeline efficiency by 60%. - Strengthened product reliability by increasing test coverage by 25% through new unit and integration tests. - Deployed Prometheus monitoring and alerting, cutting system troubleshooting time by 30%.

- Contributed to the design and development of data ingestion and transformation pipelines supporting analytics and monitoring systems. - Assisted in building data ingestion workflows using Rust and Apache Kafka to process large-scale streaming data. - Supported the implementation of data quality validation scripts that improved pipeline reliability by 25%. - Collaborated on containerizing data services with Docker and automating deployments through GitHub Actions.

- Developed and optimized computer vision models to enhance automation and object detection for smart agriculture systems. - Designed and trained YOLO-based object detection models, increasing detection accuracy by 40%. - Built data preprocessing and augmentation pipelines that improved model performance by 20%. - Collaborated with the IoT team to deploy deep learning models on embedded devices, reducing response time by 15%. - Conducted performance evaluation and real-time testing to ensure robustness under field conditions.

- Supported the deployment, maintenance, and troubleshooting of telecommunication infrastructure to ensure network reliability and performance. - Assisted in configuring and testing fiber-optic and copper network connections, improving signal stability across client installations. - Monitored network performance metrics and contributed to fault detection and resolution. - Participated in on-site maintenance and cabling operations, ensuring compliance with safety and quality standards. - Collaborated with senior engineers to document network configurations and streamline field reporting processes.