Google Cloud Data Engineer in भारत

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Google Cloud Data Engineer based in India. In this role, you will design, build, and maintain scalable data platforms on Google Cloud, helping organizations transform complex data into reliable, accessible, and valuable business assets. You will develop end-to-end data pipelines and architectures that support critical business operations, including projects for clients in regulated industries. Your work will focus on data quality, governance, performance, and cost efficiency, ensuring information remains accurate, secure, and compliant with regional requirements. Using strong SQL and Python skills, you will build robust data processing solutions that can handle real-world challenges such as delayed, duplicated, and inconsistent data. You will collaborate with clients and Google Cloud teams to make sound technical decisions, communicate architectural trade-offs, and deliver dependable solutions. This remote opportunity offers exposure to large-scale data engineering projects across multiple industries, with the autonomy to take ownership of platforms that clients rely on every day. Accountabilities - Design, develop, and maintain end-to-end data platforms on Google Cloud, translating business requirements into scalable and reliable technical solutions. - Build, orchestrate, and optimize data pipelines for data ingestion, transformation, validation, and delivery across diverse data sources. - Develop complex SQL queries and Python-based processing solutions to support efficient data transformation, analysis, and integration. - Design resilient data processing workflows that handle late-arriving records, duplicate entries, inconsistent formats, and other real-world data quality challenges. - Develop effective data models and architectures that maintain clarity, consistency, and performance as data volumes and business requirements grow.

- Optimize data processing performance, resource utilization, and cloud infrastructure costs while maintaining reliability and scalability. - Implement data quality checks, validation mechanisms, governance practices, and monitoring processes to ensure data accuracy and consistency. - Apply appropriate cloud networking, security, access control, and data protection practices to ensure information remains within approved security and geographic boundaries. - Support data residency, governance, and compliance requirements, particularly for clients operating in regulated industries. - Collaborate with clients, Google Cloud teams, and other technical stakeholders to gather requirements, explain architectural trade-offs, and align technical solutions with business objectives. - Troubleshoot pipeline failures, investigate data discrepancies, and continuously improve the reliability and efficiency of production data systems. - Take end-to-end ownership of delivery, from solution design and implementation to deployment, maintenance, and ongoing optimization. Requirements - Between 3 and 10 years of experience in data engineering , with hands-on experience designing, building, and maintaining data solutions on Google Cloud. Technical depth and demonstrated expertise are valued more highly than years of experience alone. - Strong proficiency in SQL, including complex queries, data transformations, performance tuning, and efficient data processing. - Advanced Python skills for developing data pipelines, implementing processing logic, automating workflows, and building maintainable engineering solutions. - Practical experience with Google Cloud Platform (GCP) services and tools used to build, deploy, and operate data platforms. - Solid understanding of data engineering fundamentals, including data ingestion, transformation, pipeline orchestration, data modeling, and distributed processing concepts.