Rather, it’s about gathering experience and developing skills - like a solid background in Java, Python, ETL, Hadoop, Spark, Yarn and Kafka, RDBMS and SQL systems and analytics platforms - which you might come by through a combination of school, bootcamps, online classes or prior work experience. Like a lot of fields in data science, there’s not just one singular path that all prospective data architects need to take. Six Steps to Launching a Successful Data Architect Career
