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A decade ago, Picnic set out to reinvent grocery shopping with a tech-first, customer-centric approach. For instance, we built self-service tools for all our engineers that allow them to handle tasks like environment setup, database management, or feature deployment effectively.
Data Engineering is typically a softwareengineering role that focuses deeply on data – namely, data workflows, data pipelines, and the ETL (Extract, Transform, Load) process. According to reports by DICE Insights, the job of a Data Engineer is considered the top job in the technology industry in the third quarter of 2020.
Engineers work with Data Scientists to help make the most of the data they collect and have deep knowledge of distributed systems and computer science. In large organizations, data engineers concentrate on analytical databases, operate data warehouses that span multiple databases, and are responsible for developing table schemas.
Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing. While they might be more experienced than most data engineers, they need a solid understanding of systems design.
In that case, Data Science is a comparatively broader and generalist role than Machine Learning Engineer, which is quite a specialist role and, therefore, sees a lot more vacancies, according to Indeed. In contrast, the salary of a Machine Learning Engineer with less than 1 year of experience ranges from ₹ 3.1 Lakh to ₹ 21.8
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