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Google Cloud Platform Data Engineer- Onsite (Atlanta/NJ)-Experience-12+ Years- need only locals or near by and need F2F interview for client round-Google Cloud Platform Certification mandatory. Kindly share profiles at 12+ years experience Locals Preferred We are seeking a skilled Google Cloud Platform (Google Cloud Platform) Data Engineer to design, build, and optimize data pipelines and analytics solutions in the cloud. The ideal candidate must have hands-on experience with Google Cloud Platform data services, strong ETL/ELT development skills, and a solid understanding of data architecture, data modeling, data warehousing and performance optimization. Key Responsibilities: • Develop ETL/ELT processes to extract data from various sources, transform it, and load it into BigQuery or other target systems. • Build and maintain data models, data warehouses, and data lakes for analytics and reporting. • Design and implement scalable, secure, and efficient data pipelines on Google Cloud Platform using tools such as Dataflow, Pub/Sub, cloud run, Python and linux scripting. • Optimize BigQuery queries, manage partitioning and clustering, and handle cost optimization. • Integrate data from on-premise and cloud systems using Cloud Storage, and APIs. • Work closely with DevOps teams to automate deployments using Terraform, Cloud Build, or CI/CD pipelines. • Ensure security and compliance by applying IAM roles, encryption, and network controls. • Collaborate with data analysts, data scientists, and application teams to deliver high-quality data solutions. • Implement best practices for data quality, monitoring, and governance. Required Skills and Experience: • Bachelor’s degree in Computer Science, Information Technology, or related field. • Minimum 8 years of experience in data engineering, preferably in a cloud environment. • Minimum 3 years of hands-on and strong expertise in Google Cloud Platform services: o BigQuery, Cloud storage, Cloud run, Dataflow, Cloud SQL, AlloyDB, Cloud Balancer, PubSub, IAM, Logging and Monitoring. • Proficiency in SQL, Python and Linux scripting. • Prior experience with ETL tools such as Datastage, Informatica, SSIS • Familiarity with data modeling (star/snowflake) and data warehouse concepts. • Understanding of CI/CD, version control (Git), and Infrastructure as Code (Terraform). • Strong problem-solving and analytical mindset. • Effective communication and collaboration skills. • Ability to work in an agile and fast-paced environment. • Google Cloud Platform Professional Data Engineer or Cloud Architect certification is a plus.