This is a remote position.
KANINI is seeking a highly skilledSenior Data Engineer with deep expertise in Google 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 pipelines on GCP
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data processing
- Build high-performance data transformations usingPython and PySpark
- Develop and optimizecomplex SQL queries for analytical workloads
- Work extensively withBigQuery for 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 pipelines using Git-based tools
- Ensuredata security, governance, and access control using 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 with Cloud Composer (Airflow) for orchestration
- Experience working withGoogle Cloud Storage (GCS)
- Knowledge of version 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
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