Google Cloud Platform Python Data Engineer

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