Part 5/13:
While technical details may vary based on organizational context, the importance of modularity and understanding platform limitations was highlighted. Breaking down workflows into smaller, manageable tasks not only simplifies management but also prepares teams for change. Additionally, data engineers must possess in-depth knowledge of their platform's capabilities and constraints, including resource limitations and cost factors. This understanding enables optimal utilization of technology stacks within organizational boundaries, ensuring systematic automation and continuous data flow that accommodates incremental data needs over time.