new services, libraries, tools, frameworks for data processing or management • Own and maintain the key data processing portfolios such as APIs for accessing data, ETLs for processing data, storages/DBMS for hosting data and underlying hardware and software architectures, to build durable and scalable data platform as services https://smartnews.workable.com/j/AAD9A917A8
Tests 2. Use a Version Control System 3. Branch and Merge 4. Use Multiple Environments 5. Reuse & Containerize 6. Parameterize Your Processing 7. Work Without Fear™ https://www.dataopsmanifesto.org/ https://datakitchen.readme.io/docs/seven-steps-to-dataops