Data Science Engineer (Permanent)

Data Engineer II Experience: 2 - 6 Years Exp Shift : 9:30 AM to 6:30 PM IST Placement Type: Permanent (*Kafka, Amazon AWS, GCP, Redshift, AWS Redshift Data Engineer II who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. We are looking for an experienced Data Engineer having experience in building large-scale data pipelines and data lake ecosystems. Even though you will be a part of the backend team, you will be working with cross-functional teams across the org. This role demands good hands-on different programming languages, especially Python, and the knowledge of technologies like Kafka, AWS Glue, Cloudformation, ECS, etc. You will be spending most of your time on facilitating seamless streaming, tracking, and collaborating huge data sets. This is a back-end role, but not limited to it. You will be working closely with producers and consumers of the data and build optimal solutions for the organization. Will appreciate a person with lots of patience and data understanding. Design and build systems to efficiently move data across multiple systems and make it available for various teams like Data Science, Data Analytics, and Product. Design, construct, test, and maintain data management systems. Understand data and business metrics required by the product and architect the systems to make that data available in a usable/queryable manner. Recommend different ways to constantly improve data reliability and quality. • Bachelors/Masters, Preferably in Computer Science or a related technical field. • 2-5 years of relevant experience. • Deep knowledge and working experience of Kafka ecosystem. • Good programming experience, preferably in Python, Java, Go, and a willingness to learn more. • Experience in working with large sets of data platforms. • Strong knowledge of microservices, data warehouse, and data lake systems in the cloud, especially AWS Redshift, S3, and Glue. • Strong hands-on experience in writing complex and efficient ETL jobs. • Experience in version management systems (preferably with Git). • Passion for finding and sharing best practices and driving discipline for superior data quality and integrity. • Intellectual curiosity to find new and unusual ways of how to solve data management issues.

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