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# GCP Data Engineer

- **Company:** Capgemini
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $80,420.0 - $106,050.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Bash Shell, Big Data, BigQuery, Cloud Storage, Information Engineering, Extract Transform Load (ETL), Data Warehousing, Query Languages, Data Flow Control, Python (Programming Language), Machine Learning, Cloudera, Shell Script, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Data Processing, Google Cloud, Data Storage Technologies, Data Ingestion, Apache Spark, Event Driven Architecture, Data Lakes, Pyspark, Deployment Automation, Google Cloud Functions, Terraform, Data Pipelines
- **Published:** July 7, 2026
- **Apply:** https://www.capgemini.com/jobs/503823-en_US_SAPBTP/x/

## About the Role

We are seeking a highly skilled GCP Data Engineer with strong Python expertise to design, build, and optimize scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have hands-on experience developing batch and real-time data pipelines, working with large-scale datasets, and enabling analytics and AI/ML use cases., * 8+ years of overall data engineering or software engineering experience

 * 3+ years of hands-on Google Cloud Platform experience
 * 3+ years of Python development
 * 3+ years of experience building data pipelines (batch and streaming), * Experience with Dataproc (Spark/PySpark) for large-scale processing
 * Familiarity with event-driven architectures
 * Knowledge of Terraform or Infrastructure as Code
 * Understanding of cost optimization (FinOps)

## Description

* Design, build, and maintain scalable batch and real-time data pipelines using GCP services such as Dataflow, Dataproc, and Pub/Sub
 * Develop and optimize ETL/ELT workflows for structured and unstructured data processing
 * Implement event-driven data processing using Cloud Functions and Pub/Sub
 * Build and manage data ingestion frameworks for streaming and batch data sources
Data Storage & Processing

 * Design and optimize data lakes and data warehouses using BigQuery and Cloud Storage
 * Develop efficient data models to support analytics, reporting, and machine learning workloads
 * Optimize performance and cost of data pipelines and queries
Development & Automation

 * Develop reusable and scalable solutions using Python
 * Automate workflows and orchestration using Cloud Composer (Airflow)
 * Implement CI/CD pipelines and deployment automation
Collaboration & Support

 * Collaborate with analytics, AI/ML, and business teams for data consumption needs
 * Troubleshoot data issues and perform root cause analysis
 * Continuously improve pipeline reliability, scalability, and performance

Required Technical Skills

 * GCP Services: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions (Gen2), Cloud Composer (Airflow), Cloud Storage, Cloud SQL
 * Programming: Python (advanced)
 * Query Language: SQL (advanced)
 * Data Processing: Batch & Streaming architectures
 * Scripting: Bash/Shell scripting
 * Concepts: Data Warehousing, ETL/ELT, Data Lake / Lakehouse architectures


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