Cloud Data Engineer: GCP Pipelines & Data Lakes

Capgemini; New York (NY); Hybrid; USD 75,000 - 96,000; Full time

Benefits offered by this job

Paid time off

Medical coverage

Retirement savings plans

Job summary

Capgemini is seeking a Data Engineer in New York to design and implement scalable data pipelines across batch and streaming workloads on Google Cloud Platform. You’ll work with analytics, AI/ML teams and business stakeholders to deliver reliable data products.

You will develop using Python, build ETL/ELT processes, and optimize data lakes and warehouses with BigQuery and Cloud Storage, while enabling CI/CD via Cloud Composer/Airflow.

Qualifications

• 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).

Responsibilities

• Develop and optimize ETL/ELT workflows for structured and unstructured data processing using GCP services.
• 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 ML workloads.
• Collaborate with analytics, AI/ML, and business teams for data consumption needs.

Skills

Python development

SQL

Data engineering

ETL/ELT design

Data architectures

Tools

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Functions

Cloud Composer (Airflow)

Cloud Storage

Cloud SQL

Job description

Capgemini is seeking a Data Engineer in New York to design and implement scalable data pipelines across batch and streaming workloads on Google Cloud Platform. You’ll work with analytics, AI/ML teams and business stakeholders to deliver reliable data products.

You will develop using Python, build ETL/ELT processes, and optimize data lakes and warehouses with BigQuery and Cloud Storage, while enabling CI/CD via Cloud Composer/Airflow.