- Leading appraisal and comparison for a big data processing engine to replace Redshift and transition to a data lake infrastructure. We chose Spark, which improved performance by up to 4X in our ETL queries.- Building the data CI\CD process and dev\staging environments, that greatly helped developers test their changes on real data before going to production.- Owning the developer experience Domain, developing tools and methodologies to help increase development velocity, like dedicated airflow deployments on Kubernetes for each developer.- Migrating our full production AWS based data stack, into multiple AWS accounts for disaster recovery, and transitioning to Infrastructure as code framework using Terraform.

- Development of machine learning models from research to production, which improved customer retention and conversion.- Enabling data driven decision making by building dashboards and defining new KPI’s, which helped drive impact and transparency across the company.- Building data pipelines and scripts for data warehouse management on AWS.

- Development and maintenance of ontological models, which power natural language understanding of e-commerce search- Leadership of the search evaluation team, where I was responsible for defining the product measurement and evaluation process, related tools and KPIs- Data analysis using python and SQL to support planning and prioritization of the team's work- Peer programing with senior data scientists to create new tools and improve data driven processes

- Managing an full life cycle of BI Implementation for multiple companies within the group, from requirement analysis through design, ETL, development, testing and fine tuning.- Designing key actionable reports for sales, purchasing, inventory management, warehouse management and more.- Defining business metrics and KPI's for monitoring.- Building annual budgets for multiple companies within the group.