Data Engineer – Google Cloud Platform

Remote • Posted 10 hours ago • Updated 10 hours ago

Contract Independent

Contract W2

No Travel Required

Remote

Depends on Experience

Fitment

Dice Job Match Score™

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Job Details

Skills

Google Cloud
Data Warehouse
Data Architecture
Data Flow
Cloud Computing

Summary

Job Summary

KANINI is seeking a highly skilled 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

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 10125806
Position Id: 8933846
Posted 10 hours ago

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Data Engineer – Google Cloud Platform

Dice Job Match Score™

Job Details

Skills

Summary

Job Summary

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

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