

KANINI
GCP Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a GCP Data Engineer, remote in Denver, CO, with a contract length of "unknown." Pay rate is "unknown." Key skills include GCP, BigQuery, PySpark, Dataflow, Airflow, and Medallion Architecture. Strong SQL proficiency required.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
July 24, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Remote
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Denver, CO
-
🧠 - Skills detailed
#Scrum #Version Control #Batch #Data Storage #Scala #Google Cloud Storage #Data Architecture #Python #IAM (Identity and Access Management) #Data Quality #PySpark #Data Transformations #BigQuery #SQL (Structured Query Language) #Spark (Apache Spark) #Data Pipeline #"ETL (Extract #Transform #Load)" #Airflow #Data Engineering #Clustering #Data Security #Apache Airflow #Agile #GCP (Google Cloud Platform) #GIT #Programming #Data Lake #SQL Queries #Data Governance #Cloud #Storage #Security #Data Processing #Dataflow
Role description
Hi,
We have an exciting opportunity that aligns with your skills and experience. We believe this could be a great fit for you. Kindly go through the details mentioned below.
Data Engineer - GCP
Location: Denver, CO - Remote
Job Summary
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.
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 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
Required Skills & Experience
• 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
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
Hi,
We have an exciting opportunity that aligns with your skills and experience. We believe this could be a great fit for you. Kindly go through the details mentioned below.
Data Engineer - GCP
Location: Denver, CO - Remote
Job Summary
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.
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 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
Required Skills & Experience
• 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
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





