Data Engineer

Collaborative working with the client's technology and business staff day-to-day Codes, tests, debugs, implements, and documents complex global applications. Negotiate features and associated priorities and help the team and their customers reach consensus. Develops and / or leads the development of prototypes, Identify problem causality, business impact and root causes. Coming up with exact solutions for problems related to object identity and error handling. Minimum 5 years of work experience in building data pipelines using Python, PySpark, DJango. Should have hands on experience on the MLOps. Hands-On experience in working with Python and related packages (like NumPy, pandas etc.) to load and scrap the data. Hands-on experience with at least one of the tools the Hadoop eco-system (HDFS, AWS Glue, MapReduce, Yarn, Hive, Pig, Impala, Spark, Kafka). Working experience on Relational / Non-relational databases and familiarity with data model concepts Working exposure in blending as part of larger scrum team and understanding of related scrum ceremonies Working knowledge of Unix / Linux. Knowledge of cloud platforms (e.g., AWS, Azure, GCP)