Mike Arsov
About Mike Arsov
Mike Arsov serves as the ETL Lead at Next Pathway Inc. in Toronto, Ontario, where he has worked since 2021, bringing extensive experience in ETL development and data analysis from various organizations.
Work at Next Pathway
Mike Arsov serves as the ETL Lead at Next Pathway Inc. since 2021. In this role, he is responsible for overseeing the design and development of ETL processes, ensuring efficient data integration and transformation. His work contributes to the company's data management strategies in Toronto, Ontario, Canada.
Previous Employment History
Prior to his current position, Mike Arsov held various roles in the data management field. He worked at Honda Canada Inc. as an ETL & Data Analyst from 2019 to 2021. His experience also includes a short tenure at LifeWorks as an ETL DataStage Developer in 2021. He has held multiple positions at Innovapost, Ontario Securities Commission, BMO Financial Group, and other organizations, focusing on ETL DataStage development and data analysis.
Education and Expertise
Mike Arsov earned his Bachelor's degree from the University of Waterloo, studying from 2001 to 2006. He has expertise in designing and developing ETL jobs for complex transformations and loading data into Enterprise Data Warehouses (EDW) or Data Marts. His skills include data modeling using Erwin, with proficiency in dimensional modeling, Star Schema modeling, and Snowflake modeling.
Technical Skills and Proficiencies
Mike possesses strong troubleshooting and debugging skills in SQL, T-SQL, and Stored Procedures. He is experienced in programming languages such as VBScript, ASP, PHP, and JavaScript, allowing him to approach problems analytically. He is proficient in using IBM-Ascential DataStage 7.5/8.0 for developing Data Warehousing and Business Intelligence applications.
Data Warehousing Techniques
Mike Arsov has extensive experience in data warehousing techniques, including Data Cleansing, Slowly Changing Dimensions, Surrogate key assignment, and Change Data Capture (CDC). His knowledge in these areas supports the effective management and transformation of data within organizations.