GCP Data Engineer (L4)

Job Overview We are looking for an experienced GCP Data Engineer with 812 years of experience in designing, architecting, and implementing end-to-end data engineering solutions on Google Cloud Platform. The ideal candidate should have strong expertise in building scalable data pipelines, cloud-native data integration frameworks, data warehousing, and real-time data processing using GCP services. Key Responsibilities Design, architect, and implement end-to-end data engineering solutions on Google Cloud Platform. Build scalable and high-performance data pipelines using Apache Beam, Google Dataflow, Apache Spark, and Dataproc. Develop and optimize data models, ETL/ELT processes, and cloud-based data integration frameworks. Implement automated data ingestion, transformation, validation, and enrichment pipelines. Work with structured and unstructured datasets to support analytics, reporting, and business intelligence initiatives. Develop solutions using BigQuery, Cloud Storage, Pub/Sub, Cloud Functions, Dataproc, Bigtable, Cloud SQL, Spanner, and Datastore. Ensure data quality, governance, security, and compliance requirements are met during data migrations and integrations. Collaborate with cross-functional teams to design scalable cloud-native architectures and best practices. Optimize pipeline performance, reliability, and cost efficiency across GCP environments. Support production deployments, troubleshooting, and continuous improvement of data platforms.