Summary
Mohammad Khelghati is a Data, Analytics & AI Solutions Architect with 11 years of experience helping enterprises turn complex data into actionable outcomes, currently driving technical strategy and sales enablement for Databricks' Lakehouse Platform. He blends a strong research foundation—holding PhD-level experience in web data monitoring, information retrieval and extraction—with hands-on delivery of ML and cloud solutions across industries including FMCG, tobacco, and brewing. At HEINEKEN and Philip Morris he led model adoption and analytics programs; at Deloitte he designed IoT and cloud architectures and scaled internship and team programs. Comfortable in multicultural environments across Sweden, Germany, Austria and the Netherlands, he combines technical depth (Hadoop, Spark ecosystem, Azure, R/Python) with product-minded consulting and team leadership. Notably, his academic work on deep web entity monitoring informs a practical focus on reliable data ingestion and change detection in production systems. He is as comfortable advising customers through technical evaluations as he is rolling up his sleeves to implement end-to-end analytics pipelines.
11 years of coding experience
10 years of employment as a software developer
KTH Royal Institute of Technology
Bachelor of Science, Engineering of Information Technology, A, Bachelor of Science, Engineering of Information Technology, A at Institute for Advanced Studies in Basic Sciences, Zanjan
Ph.D. Candidate, Computer Science, Ph.D. Candidate, Computer Science at University of Twente
Master Thesis, Enabling Structured Queries over Text Crossing Structure Chasm in Dataspaces, Master Thesis, Enabling Structured Queries over Text Crossing Structure Chasm in Dataspaces at Rheinisch-Westfälische Technische Hochschule Aachen
High School, Mathematics, High School, Mathematics at National Organization for Exceptional Talents (NODET)
English, Persian, Turkish, Dutch