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# Lead Data Engineer

- **Company:** Capgemini
- **Location:** United States
- **Experience:** Expert
- **Salary:** $130,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Airflow, Big Data, BigQuery, Cloud Database, Information Systems, Computer Programming, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Warehousing, DevOps, Distributed Computing Environment, Data Flow Control, Python (Programming Language), Cloud Services, Cloudera, SQL Databases, Google Cloud, Real Time Systems, Apache Spark, Multi-Cloud, Infrastructure as Code (IaC), Git, Information Technology, Data Management, Terraform, Software Version Control, Data Pipelines, Apache Beam
- **Published:** August 7, 2026
- **Apply:** https://www.dice.com/job-detail/d56a180e-4eb3-41ad-8e07-d09fa66c6d57

## About the Role

We are seeking a highly skilled Senior Data Engineer with strong expertise in Google Cloud Platform (Google Cloud Platform) to design, develop, and optimize enterprise-scale data platforms and data processing pipelines. The ideal candidate will have extensive experience in cloud-native data engineering, distributed computing frameworks, modern DevOps practices, and data governance. This role requires both hands-on technical proficiency and leadership capabilities to drive best practices across the data engineering organization.

Must Have

Google Cloud Platform Certifications (e.g., Professional Data Engineer).
Experience with real-time processing, Vertex AI, or multi-cloud environments, * Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.

 * 8+ years of experience in data engineering, data warehousing, or big data technologies.
 * Strong programming skills in:
 + SQL
 + Python
 + Java and/or Scala
 * Hands-on experience with distributed data processing frameworks:
 + Apache Spark
 + Apache Beam
 * Proven expertise with Google Cloud Platform services:
 + BigQuery
 + Dataflow
 + Dataproc
 + Pub/Sub
 + Composer (Airflow)
 + Terraform
 * Experience with DevOps practices including:
 + CI/CD pipelines
 + Git-based source control
 + Infrastructure as Code (IaC)
 * Strong understanding of data modeling, ETL/ELT frameworks, and cloud data architectures.



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