Source description
About the role
Key Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines using Python, SQL, and Java on Google Cloud Platform (BigQuery, Dataflow, Composer) . Lead migration of legacy on-premise data warehouses and BI datasets to cloud-native architectures. Build reliable, high-performance data models and data pipelines to support enterprise analytics and financial reporting. Monitor, troubleshoot, and optimize production data pipelines and ingestion processes. Collaborate with Finance, Analytics, Supply Chain, and global business teams to deliver scalable data solutions. Implement data quality, validation, reconciliation, monitoring, and governance frameworks. Drive engineering excellence through CI/CD, automation, reusable frameworks, and cloud best practices. Develop dashboards and reporting solutions using Looker/Looker Studio and semantic models (LookML). Mentor junior engineers and contribute to technical capability building within the team. Required Skills 7+ years of experience in Data Engineering/Data Warehousing. 3+ years of hands-on experience with Google Cloud Platform (GCP) . Strong expertise in SQL , Python , and Java . Experience with BigQuery, Dataflow, Composer , ETL/ELT pipeline development, and cloud migration. Strong knowledge of data modeling, data governance, metadata management, and data quality frameworks. Hands-on experience with Looker/Looker Studio and LookML . Experience with CI/CD , Git, and deployment automation.