Google Cloud Platform Data Engineer
Why This Role Stands Out
This hybrid Google Cloud Platform Data Engineer role at Kanini offers an exciting opportunity to build scalable data solutions and advance your expertise in modern data architecture. If you thrive on designing robust data pipelines and optimizing performance within a collaborative environment, this position is perfect for you to make a significant impact. Apply today to join a forward-thinking company and leverage your skills in BigQuery, PySpark, and Dataflow.
Quick Overview
Job Description
Role: Google Cloud Platform Data Engineer
We are looking for Data Engineer with deep expertise in Google Cloud Platform (Google Cloud Platform) and modern data architecture. The ideal candidate will have hands-on experience designing scalable data pipelines, implementing Medallion Architecture, and building robust enterprise-grade data solutions.
This role requires strong technical proficiency in BigQuery, PySpark, Dataflow, and Airflow, along with a solid understanding of cloud data governance, performance optimization, and CI/CD practices.
Key Responsibilities
- Design, develop, and maintain scalable batch and real-time data pipelines on Google Cloud Platform
- Implement and manage Medallion Architecture (Bronze, Silver, Gold layers) for data processing
- Build high-performance data transformations using Python and PySpark
- Develop and optimize complex SQL queries for analytical workloads
- Work extensively with BigQuery for large-scale data processing and performance tuning
- Develop and deploy pipelines using Cloud Dataflow
- Orchestrate workflows using Cloud Composer (Apache Airflow)
- Manage data storage and lifecycle using Google Cloud Storage (GCS)
- Implement version control and CI/CD pipelines using Git-based tools
- Ensure data security, governance, and access control using Google Cloud Platform IAM
- Optimize data solutions for performance, scalability, reliability, and cost-efficiency
Required Skills & Experience
- Strong hands-on experience with Google Cloud Platform (Google Cloud Platform)
- Expertise in BigQuery (partitioning, clustering, query optimization)
- Proven experience implementing Medallion Data Architecture
- Strong programming skills in Python and PySpark
- Advanced proficiency in SQL (complex joins, window functions, performance tuning)
- Hands-on experience with Cloud Dataflow
- Experience with Cloud Composer (Airflow) for orchestration
- Experience working with Google Cloud Storage (GCS)
- Knowledge of version control systems (Git) and CI/CD practices
- Strong understanding of Google Cloud Platform IAM and cloud security best practices
Preferred Qualifications
- Experience working with large-scale enterprise data platforms
- Knowledge of data warehousing and data lake concepts
- Familiarity with real-time streaming frameworks
- Experience in data governance and data quality frameworks
- Exposure to Agile/Scrum methodologies
Skills
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