Data professional with 13+ years of experience in technology and process optimization, currently focused on Data Engineering, Lakehouse architectures, Streaming Data Pipelines and AI-powered analytics solutions.
I enjoy building scalable cloud-native data platforms using AWS, Databricks, Apache Spark, Kafka and modern Data Engineering practices.
- Apache Spark
- PySpark
- Delta Lake
- Databricks
- Apache Kafka
- Apache Airflow
- SQL
- Data Modeling
- AWS S3
- AWS EC2
- AWS IAM
- AWS Glue
- Python
- SQL
- JavaScript
- TypeScript
- MLflow
- Machine Learning
- Data Quality
- Generative AI
Real-time streaming data platform simulating predictive maintenance for ATM networks.
Technologies
- Apache Kafka
- Apache Airflow
- AWS S3
- Databricks
- Delta Lake
- PySpark
🔗 Repository:
https://github.com/ElipechukIgor/atm-predictive-maintenance-platform
End-to-end Lakehouse architecture for insurance claim image processing and AI-powered classification.
Technologies
- AWS S3
- Databricks Auto Loader
- Delta Lake
- MLflow
- Databricks Workflows
- Computer Vision
🔗 Repository:
https://github.com/ElipechukIgor/smart-claims-image-pipeline
- Advanced Databricks
- Spark Optimization
- Data Quality Engineering
- MLOps
- Streaming Architectures
- Generative AI
www.linkedin.com/in/igor-elipechuk
https://github.com/ElipechukIgor
⭐ Always learning, building and sharing Data Engineering projects.