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
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💰 - Day rate
Unknown
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🗓️ - Date
July 24, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Remote
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Denver, CO
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🧠 - 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