GCP Python Data Engineer: Build Scalable Data Pipelines

Capgemini; New York (NY); On-site; USD 115,000 - 145,000; Full time

Job summary

Capgemini in the United States is seeking a GCP Python Data Engineer to design, build, and optimize scalable cloud-based data solutions. You will develop ETL/ELT pipelines and collaborate with analytics teams and data scientists.

The role emphasizes batch and real-time data workflows, data lakehouse architectures, and CI/CD practices to ensure reliable, secure, and cost-efficient data platforms.

Qualifications

• 5+ years of data engineering or related experience.
• 2+ years hands-on Google Cloud Platform (GCP) experience.
• 2+ years professional Python development experience.
• Experience building batch and real-time data pipelines.
• Strong SQL development and data warehousing knowledge.

Responsibilities

• Design, build, and optimize ETL/ELT pipelines on GCP.
• Develop batch and streaming data processing solutions.
• Create data lakehouse/data warehouse models for analytics and AI/ML.
• Implement CI/CD and observability practices.

Skills

Python development

Data engineering

SQL development

Cloud architecture

ETL/ELT design

Tools

GCP (Google Cloud Platform)

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Functions

Cloud Composer (Airflow)

Cloud Storage

Job description

Capgemini in the United States is seeking a GCP Python Data Engineer to design, build, and optimize scalable cloud-based data solutions. You will develop ETL/ELT pipelines and collaborate with analytics teams and data scientists.

The role emphasizes batch and real-time data workflows, data lakehouse architectures, and CI/CD practices to ensure reliable, secure, and cost-efficient data platforms.