Jeffrey Smith

Jeffrey Smith

Data Engineer @ Walker Edison

About Jeffrey Smith

Jeffrey Smith is a Data Engineer with a background in Information Technology and Systems. He has worked at Walker Edison since 2021 and has prior experience in business intelligence and data analysis roles across several companies.

Work at Walker Edison

Jeffrey Smith has been employed as a Data Engineer at Walker Edison since 2021. In this role, he focuses on building data pipelines and integrating APIs, utilizing his expertise in various data engineering tools and technologies. His contributions to the company involve leveraging cloud platforms and data orchestration tools to enhance data management processes.

Education and Expertise

Jeffrey Smith studied at Collin County Community College, where he earned an Associate of Arts (A.A.) degree from 2011 to 2015. He then attended the University of Texas at Dallas - Naveen Jindal School of Management, achieving a Bachelor of Science (B.S.) in Information Technology and Systems from 2015 to 2018. Additionally, he has expertise in using Ubuntu for data engineering tasks and is skilled in automation tools such as UI Path and Blue Prism.

Background

Jeffrey Smith's professional background includes various roles in data analysis and business intelligence. He worked as a Business Intelligence Developer at DSI Systems Inc. for eight months in 2018, followed by a position as a Business Intelligence Analyst at ClearCorrect from 2019 to 2020. He also served as a Data Analyst at Wesco Aircraft for five months in 2019. Prior to his career in data engineering, he was self-employed as a plumber from 2015 to 2018 and worked as a delivery driver for Papa Johns from 2012 to 2015.

Technical Skills and Tools

Jeffrey Smith specializes in building data pipelines and integrating APIs using a variety of tools. His technical skill set includes proficiency in Postgres, SQL, Redshift, Python, Snowflake, AWS, and Domo. He is experienced in working with cloud platforms like AWS and data orchestration tools such as Airflow, which are essential for effective data management and engineering tasks.

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