Job Description Design, code, test and deploy production grade data engineering solutions including pipeline development, data quality frameworks, data validation and metadata management. Design and develop services/backend solutions including REST web services, spring boot and Java/Python/Scala. Design and deploy solutions onto cloud ecosystems like Azure/GCP. Collaborate with product and engineering teams across multiple zones, translate business requirements and roadmap into technical solutions. Design cost wise and compute wise efficient data engineering solutions. Architect and design automation and innovation ideas/solutions at Walmart scale that can be leveraged across multiple platforms. Possess exceptional attitude and zeal to learn new skills, optimise sys Possess strong leadership skills and have the capability to mentor team technically. Qualifications Min 11-18 years of Big data development experience using Spark, Hive, Hadoop technologies along with strong enterprise applications development background using Java/Python/Scala, REST API and Analytics. Demonstrates up-to-date expertise in designing Data Engineering solutions , including pipeline development, data quality frameworks, data validation and metadata management. Design, develop, implement and tune distributed data processing pipelines that process large volume of data; focusing on scalability, low -latency, and fault-tolerance in every system built. Demonstrates expertise in writing complex, optimised queries across large data sets Proven, working expertise with Big Data Technologies Hadoop, HDFS, Hive, Spark Scala/PySpark, and SQL Knowledge and experience in Kafka, Airflow, Druid, Presto, SPARK RAPIDS GPU, MLOps, Looker/Tableau are added advantages.