Why This Role Stands Out
Leverage your Python and Google Cloud expertise to build cutting-edge data solutions at Capgemini, with a competitive salary and bonus, and enjoy the flexibility of a hybrid work environment. This role is perfect for experienced data engineers who thrive on designing scalable pipelines and contributing to impactful analytics, AI/ML, and BI initiatives, so don't miss this opportunity to advance your career.
Quick Overview
Job Description
Location: New York, NY (Preferred) | Charlotte, NC (Relocation Considered) | Hybrid
Compensation: $110,000 - $145,000 Base Salary + 15-20% Annual Bonus
Work Authorization: Must be authorized to work in the United States without current or future sponsorship. No visa sponsorship, transfers, or C2C arrangements available.
We are seeking a hands-on Google Cloud Platform Python Data Engineer to design, develop, and optimize cloud-native data solutions supporting enterprise analytics, AI/ML, and business intelligence initiatives.
This role is ideal for a data engineering professional with strong Google Cloud Platform expertise, advanced Python development skills, and experience building scalable batch and real-time data pipelines.
Candidates may be considered at the Senior Consultant, Managing Consultant, or Senior Manager level depending on experience.
Responsibilities
- Design, build, and optimize data pipelines on Google Cloud Platform
- Develop ETL/ELT solutions using Dataflow, Dataproc, Pub/Sub, and BigQuery
- Create scalable Python-based applications and data processing frameworks
- Design and support data lake and data warehouse architectures
- Build event-driven solutions using Cloud Functions and Pub/Sub
- Automate workflows with Cloud Composer (Airflow)
- Support AI/ML and advanced analytics use cases
- Collaborate with business, analytics, and engineering teams
- Troubleshoot production issues and improve pipeline performance, reliability, and scalability
- Contribute to CI/CD and cloud deployment automation efforts
Required Qualifications
- 5+ years of data engineering or software engineering experience
- 2+ years of hands-on Google Cloud Platform experience
- 2+ years of Python development experience
- Experience developing batch and streaming data pipelines
- Advanced SQL skills
- Experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, and Airflow
- Strong understanding of ETL/ELT, data warehousing, and data lake architectures
Preferred Qualifications
- Financial Services experience preferred
- Experience with Vertex AI, Gemini, LLMs, RAG solutions, or Agentic AI frameworks
- Experience with Spark or PySpark
- Terraform or Infrastructure as Code experience
- Knowledge of cloud cost optimization and FinOps concepts
- Google Cloud Professional Data Engineer certification
- Experience supporting AI/ML data platforms
No Sponsorship
Candidates must be authorized to work in the United States without sponsorship now or in the future. This role is not available for H-1B, OPT, CPT, TN, E-3, L-1, or other employment-based visa holders requiring sponsorship.
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