AI Google Cloud Platform

5+ years of data engineering experience, including hands-on experience with Hadoop and Google Cloud data solutions; creating and supporting Spark-based processing and Kafka streaming in a highly collaborative team. 2+ years of hands-on experience developing data flows using Kafka, Flink, and Spark Streaming. 3+ years of experience with data lakehouse architecture and design, including hands-on experience with Python, PySpark, Apache Kafka, Airflow, SQL, Google Cloud Platform Cloud Storage, BigQuery, Dataproc, and Cloud Composer. 2+ years of experience working with NoSQL databases, such as columnar, graph, document, and key-value databases, and associated data formats. Public cloud certifications, such as Google Cloud Platform Professional Data Engineer, Azure Data Engineer, or AWS Specialty Data Analytics. Proven skills in data migration from on-premises to cloud-native environments. Proven experience with Hadoop ecosystem capabilities, such as Hive, HDFS, Parquet, Iceberg, and Delta Tables. Deep understanding of data warehousing, cloud data architecture, data pipeline development, and orchestration. Experience designing and implementing highly scalable, modular data pipelines with built-in data controls to automate data governance. Familiarity with GenAI frameworks, such as LangChain and LangGraph, for developing agent-based data capabilities. Experience with DevOps and CI/CD deployments, including Git, Jenkins, Docker, and Kubernetes. Web-based UI development using React and Node.js is a plus.