Raw LLM Responses

I have been an ETL/Data Engineer and architect for 20+ years. What I know is all ML systems need good quality data. Even then they are not good enough today. I know a lot of Data engineering is geared towards ML projects nowadays. But what I have seen in last 20 years is constant issues with data quality and data governance. Also most work involves repeating similar ETL work over and over again and upgrading tool/db versions or lift and shift work. Where I expect to see more involvement of ML is in the second part. They were already automated by large consulting companies before age of ML anyway. What will revolutionize the industry and will reduce the need of data engineers are automation of data quality and data governance. Most ETL and pipeline exists to work around problems caused by missing these. One constant source of work has been government regulations. With better data quality and data governance even many of those will become automated. At that stage I will start fearing for my job