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# Lead Data Engineer - GCP Data Architect

- **Company:** Capgemini
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $144,890.0 - $190,117.0
- **Contract:** Permanent contract
- **Skills:** Big Data, BigQuery, Code Review, Continuous Integration, Data Architecture, Information Engineering, Extract Transform Load (ETL), Data Systems, DevOps, Distributed Computing Environment, Distributed Systems, Data Flow Control, Python (Programming Language), Cloud Services, Software Deployment, Data Streaming, Data Processing, Google Cloud, Cloud Platform System, Build Management, Infrastructure Automation Frameworks, Real Time Data, Data Management, Data Pipelines
- **Published:** September 11, 2026
- **Apply:** https://www.careerjet.com/job/us1077d34dcbc85a356ade3e0f09591e37/eaa

## About the Role

* 7+ years of experience in Data Engineering, Data Architecture, or Cloud Data Platform development.
 * Strong hands-on experience with:

 * BigQuery
 * Dataflow
 * Pub/Sub
 * Python
 * Experience designing and implementing data solutions on Google Cloud Platform (GCP).
 * Strong understanding of:

 * Distributed systems
 * Data pipeline architecture
 * Batch and streaming processing patterns
 * Large-scale data processing and analytics
 * Experience developing and supporting production-grade data pipelines.
 * Ability to balance architectural strategy with hands-on implementation.
 * Strong communication and stakeholder management skills.

## Description

We are seeking a hands-on GCP Data Architect to design and build scalable, cloud-native data solutions on Google Cloud Platform. This role requires strong expertise in BigQuery, Dataflow, Pub/Sub, and Python, along with a solid understanding of distributed systems, batch and streaming data architectures, and modern data engineering practices. The ideal candidate is both an architect and a doer, capable of guiding technical direction while actively contributing to implementation and delivery.
Your role

 * Design and architect scalable, secure, and cost-effective data platforms on Google Cloud Platform.
 * Lead the development of batch and real-time data ingestion and processing solutions.
 * Design modern data architectures leveraging BigQuery, Dataflow, Pub/Sub, and related GCP services.
 * Evaluate and implement appropriate distributed processing and data movement patterns for varying business requirements.
 * Develop and optimize enterprise-scale ETL/ELT pipelines.
 * Collaborate with data engineers, application developers, platform teams, and business stakeholders.
 * Provide architectural guidance for data modeling, storage, governance, performance, and scalability.
 * Support cloud-native application deployment patterns using Cloud Run and/or GKE.
 * Contribute to infrastructure automation, DevOps, and CI/CD best practices.
 * Participate in architecture reviews, technical design sessions, and code reviews.
 * Troubleshoot and optimize data processing workloads and platform performance.


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