Data Engineer

Capgemini•New York, NY

11d•$75,000 - $96,000•Remote

About The Position

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.

Requirements

5+ years of overall data engineering or software engineering experience
2+ years of hands-on Google Cloud Platform experience
2+ years of Python development
2+ years of experience building data pipelines (batch and streaming)

Nice To Haves

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)
Google Cloud Professional Data Engineer Certification
Experience supporting AI/ML data pipelines

Responsibilities

Develop and optimize ETL/ELT workflows for structured and unstructured data processing using GCP services such as Dataflow, Dataproc, and Pub/Sub
Implement event-driven data processing using Cloud Functions and Pub/Sub
Build and manage data ingestion frameworks for streaming and batch data sources
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
Develop solutions using Python
Automate workflows and orchestration using Cloud Composer (Airflow)
Implement CI/CD pipelines and deployment automation
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