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# Senior Google Cloud Platform Data Engineer

- **Company:** K-Tek Resourcing LLC
- **Location:** Coral Gables, FL, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Training Data, Artificial Intelligence, Airflow, Apache HTTP Server, BigQuery, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Systems, Data Flow Control, Monitoring of Systems, Python (Programming Language), Cloud Services, Cloudera, SQL Databases, Data Streaming, Enterprise Data Management, Google Cloud, Apache Spark, Pyspark, Infrastructure Automation Frameworks, Data Management, Terraform
- **Published:** November 3, 2026
- **Apply:** https://www.dice.com/job-detail/3f5e2a47-1812-4237-a090-2082111005a1

## About the Role

* 10+ years of Data Engineering experience.
 * Minimum 8+ years of hands-on Google Cloud Platform (Google Cloud Platform) experience.
 * Proven experience building large-scale enterprise data platforms.

Mandatory Technical Skills
Google Cloud Platform: BigQuery, Dataproc, Dataflow, Cloud Composer (Airflow), Pub/Sub, GCS, BigLake,
Cloud Functions, Cloud Run
Data Engineering: Python, SQL, PySpark, Apache Spark, Data Modeling, ETL/ELT, Batch &
Streaming Processing
Lakehouse & Automation: Apache Iceberg, Terraform, CI/CD, Infrastructure as Code,
Monitoring & Observability

## Description

We are looking for a hands-on Senior Google Cloud Platform Data Engineer to design, build, and optimise
enterprise-scale data platforms on Google Cloud Platform (Google Cloud Platform). The ideal candidate will
have deep expertise in BigQuery, Apache Iceberg, and cloud-native data engineering
services, with experience delivering scalable, high-performance data solutions that support
analytics, reporting, and AI-driven initiatives., * Design, develop, and maintain enterprise-scale data platforms on Google Cloud Platform.

 * Build and optimise batch and streaming data pipelines using BigQuery, Dataproc,
Dataflow, Pub/Sub, and GCS.

 * Develop robust ETL/ELT frameworks, data models, and data quality solutions.
 * Implement modern lakehouse architectures using Apache Iceberg.
 * Design and manage end-to-end orchestration using Cloud Composer (Airflow).
 * Optimise BigQuery workloads for performance, scalability, and cost efficiency.
 * Implement CI/CD pipelines, Terraform, and operational monitoring.
 * Enable trusted, governed, and AI-ready data foundations.