N2P Systems
GCP Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP Data Engineer with a contract length of "unknown" and a pay rate of "unknown". Key skills include expertise in BigQuery, PySpark, Dataflow, Airflow, and Java. Experience with Medallion Architecture and cloud data governance is required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
June 17, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United States
-
🧠 - Skills detailed
#IAM (Identity and Access Management) #Dataflow #PySpark #Scala #Data Storage #SQL (Structured Query Language) #Agile #Clustering #Apache Airflow #Data Architecture #BigQuery #GCP (Google Cloud Platform) #Google Cloud Storage #Python #Data Quality #Data Governance #GIT #Java #Storage #Airflow #Data Engineering #Security #Version Control #"ETL (Extract #Transform #Load)" #Data Processing #Spark (Apache Spark) #Cloud #Scrum #Data Pipeline #Programming #SQL Queries #Data Security #Batch #Data Transformations #Data Lake
Role description
About the Company
KANINI is seeking a highly skilled 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, implementing Medallion Architecture, and building robust enterprise-grade data solutions.
About the Role
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.
Responsibilities
• Design, develop, and maintain scalable 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 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 GCP IAM
• Optimize data solutions for performance, scalability, reliability, and cost-efficiency
Qualifications
• Strong hands-on experience with Google Cloud Platform (GCP)
• 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 GCP IAM and cloud security best practices
• Hands-on experience with Java is mandatory
Preferred Skills
• 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
About the Company
KANINI is seeking a highly skilled 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, implementing Medallion Architecture, and building robust enterprise-grade data solutions.
About the Role
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.
Responsibilities
• Design, develop, and maintain scalable 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 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 GCP IAM
• Optimize data solutions for performance, scalability, reliability, and cost-efficiency
Qualifications
• Strong hands-on experience with Google Cloud Platform (GCP)
• 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 GCP IAM and cloud security best practices
• Hands-on experience with Java is mandatory
Preferred Skills
• 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
