Poor data engineering is like building a shaky foundation for a house—it leads to unreliable information, wasted time and money, and even legal problems, making everything less dependable and more troublesome in our digital world. In the retail industry specifically, data engineering is particularly important for managing and analyzing large volumes of sales, inventory, and customer data, enabling better demand forecasting, inventory optimization, and personalized customer experiences. It helps retailers make informed decisions, streamline operations, and remain competitive in a rapidly evolving market. Insight and frameworks learned from data engineering practices can be applied to a multitude of people and problems, and in turn, learning from someone who has been at the forefront of data engineering is invaluable.

Mohammad Sabah is SVP of Engineering and Data at Thrive Market, and was appointed to this role in 2018. He joined the company from The Honest Company where he served as VP of Engineering & Chief Data Scientist. Sabah joined The Honest Company following its acquisition of Insnap, which he co-founded in 2015. Over the course of his career, Sabah has held various data science and engineering roles at companies including Facebook, Workday, Netflix, and Yahoo!

In the episode, Richie and Mo explore the importance of using AI to identify patterns and proactively address common errors, the use of tools like dbt and SODA for data pipeline abstraction and stakeholder involvement in data quality, data governance and data quality as foundations for strong data engineering, validation layers at each step of the data pipeline to ensure data quality, collaboration between data analysts and data engineers for holistic problem-solving and reusability of patterns, ownership mentality in data engineering and much more.

Links from the show:

#162 Scaling Data Engineering in Retail with Mohammad Sabah, SVP of Engineering & Data at Thrive Market

DataFramed