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Data Engineer with GCP

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Senior Software Engineer
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CREQ265698 Requisition #

Senior Data Engineer Experience 6+ Years Location Hyderabad, India Employment Type Full Time Work Model Hybrid Role Overview We are building a cloud-native AI platform on Google Cloud that powers intelligent enterprise applications. We are looking for a highly skilled Senior Data Engineer who can design scalable data architectures, build reliable data pipelines, and create robust data foundations for modern applications. This is a hands-on engineering role suited for someone who enjoys solving complex data challenges, optimizing databases, designing efficient schemas, and building scalable data platforms. You will work closely with Product Managers, Architects, AI Engineers, Software Engineers, and QA Engineers to deliver high-quality enterprise solutions. The ideal candidate should be comfortable working in a fast-paced environment, taking ownership of technical solutions, and building scalable data platforms that support AI-powered applications. Key Responsibilities Data Architecture Design scalable enterprise data architectures. Create efficient database schemas and data models for structured and unstructured data. Design and implement robust ETL/ELT pipelines. Build scalable batch and streaming data ingestion frameworks. Optimize database performance, partitioning, indexing, and query execution. Design data storage strategies that support scalability, reliability, and performance. Data Engineering Develop and maintain high-performance data pipelines. Build reusable data engineering frameworks and components. Support AI and analytics workloads with reliable and scalable data infrastructure. Automate manual data processing wherever possible. Troubleshoot production data issues and implement sustainable solutions. Google Cloud Platform Design and build scalable solutions using Google Cloud Platform services, including BigQuery Cloud Storage Dataflow Dataproc Pub/Sub Experience with Google Cloud Platform is highly preferred. Data Quality and Governance Implement data validation and quality controls. Build monitoring and alerting for data pipelines. Ensure consistency, reliability, and traceability of enterprise data. Establish best practices for data governance and lifecycle management. Performance Engineering Optimize SQL queries and database performance. Improve pipeline throughput and processing efficiency. Analyze bottlenecks and recommend scalable solutions. Engineering Excellence Develop produ

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