Sr. GCP Data Engineer

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.

• 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

• 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

• 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