This is a remote position. KANINIis seeking a highly skilledSenior Data Engineerwith deep expertise inGoogle Cloud Platform (GCP)and modern data architecture. The ideal candidate will have hands-on experience designing scalable data pipelines, implementingMedallion Architecture, and building robust enterprise-grade data solutions. This role requires strong technical proficiency inBigQuery, PySpark, Dataflow, and Airflow, along with a solid understanding of cloud data governance, performance optimization, and CI/CD practices. Key Responsibilities Design, develop, and maintainscalable batch and real-time data pipelineson GCP Implement and manageMedallion Architecture (Bronze, Silver, Gold layers)for data processing Build high-performance data transformations usingPython and PySpark Develop and optimizecomplex SQL queriesfor analytical workloads Work extensively withBigQueryfor large-scale data processing and performance tuning Develop and deploy pipelines usingCloud Dataflow Orchestrate workflows usingCloud Composer (Apache Airflow) Manage data storage and lifecycle usingGoogle Cloud Storage (GCS) Implementversion control and CI/CD pipelinesusing Git-based tools Ensuredata security, governance, and access controlusing GCP IAM Optimize data solutions forperformance, scalability, reliability, and cost-efficiency Required Skills & Experience Strong hands-on experience withGoogle Cloud Platform (GCP) Expertise inBigQuery(partitioning, clustering, query optimization) Proven experience implementingMedallion Data Architecture Strong programming skills inPython and PySpark Hands-on exposure on Java Advanced proficiency inSQL (complex joins, window functions, performance tuning) Hands-on experience withCloud Dataflow Experience withCloud Composer (Airflow)for orchestration Experience working withGoogle Cloud Storage (GCS) Knowledge ofversion control systems (Git)and CI/CD practices Strong understanding ofGCP IAM and cloud security best practices Preferred Qualifications Experience working withlarge-scale enterprise data platforms Knowledge ofdata warehousing and data lake concepts Familiarity withreal-time streaming frameworks Experience indata governance and data quality frameworks Exposure to Originally posted on Himalayas