Sr. GCP Data Engineer (Job-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