远程GCP数据工程师（职位ID 3301）

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