
Data engineering has vastly advanced with the advent of big data. Traditional manual scripting for data transformation, which required deep coding skills and database knowledge, became less feasible as data increased in size and complexity. With the emergence of ETL frameworks like Apache Spark and Apache Flink, data processing is now more efficient, addressing the need for scalability and reliability