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# Optimum - Data Engineer Google Cloud Platform

- **Company:** Capgemini
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $76,730.0 - $150,800.0
- **Contract:** Permanent contract
- **Skills:** BigQuery, Information Systems, Data as a Services, Information Engineering, Data Governance, Data Transformation, Data Mining, Data Warehousing, Database Queries, Python (Programming Language), SQL Databases, Scripting, Google Cloud, Git, Information Technology, Software Version Control, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://www.dice.com/job-detail/8a6639ad-f035-4627-b88f-e4822a33ee76

## About the Role

We are seeking a Google Cloud Platform Data Engineer with hands-on experience with Google Cloud Platform (Google Cloud Platform) services, particularly BigQuery, and be experienced in DBT for data transformation and modeling. This role requires strong SQL skills, a solid understanding of data warehousing concepts, and light proficiency in Python for scripting and automation. Strong understanding of Telco - CES and Network Data. Calls, Chats, Network data., * Bachelor's degree in Computer Science, Information Systems, or a related field.

 * 5 years of experience in data engineering or a similar role.
 * Strong expertise in SQL with the ability to write efficient, complex queries.
 * Nice to have knowledge in DBT for data modeling and transformation
 * Hands-on experience with BigQuery and other Google Cloud Platform data services.
 * Solid understanding of data warehousing principles and best practices.
 * Basic to intermediate skills in Python for scripting and automation.
 * Familiarity with version control systems like Git.
 * Excellent problem-solving and communication skills.'

## Description

* Design, build, and maintain scalable data pipelines on Google Cloud Platform, primarily using BigQuery.
 * Nice to have the experience to Develop and manage DBT models to transform raw data into clean, tested, and documented datasets.
 * Write complex and optimized SQL queries for data extraction, transformation, and analysis.
 * Implement and maintain data warehousing solutions, ensuring performance, scalability, and reliability.
 * Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions.
 * Monitor and troubleshoot data pipeline performance and data quality issues.
 * Automate data workflows and tasks using Python scripts where necessary.
 * Ensure data governance, security, and compliance standards are met.