GCP Python Data Engineer

Capgemini • New York, NY

13h • $115,000 - $145,000 • Remote

About The Position

We are seeking a highly skilled GCP Python Data Engineer to design, build, and optimize scalable cloud-based data solutions on Google Cloud Platform (GCP). The ideal candidate will possess strong Python development skills, hands-on experience with modern data engineering technologies, and expertise in building both batch and real-time data pipelines supporting analytics, AI/ML, and enterprise reporting initiatives.
Work Authorization: Candidates must be authorized to work in the United States without current or future sponsorship. No visa sponsorship, transfers, or C2C arrangements are available.

Requirements

• 5+ years of data engineering, software engineering, or related experience.
• 2+ years of hands-on Google Cloud Platform (GCP) experience.
• 2+ years of professional Python development experience.
• Experience developing batch and real-time data pipelines.
• Advanced SQL development and query optimization skills.
• Experience with data warehousing, ETL/ELT, and modern data architecture patterns.
• Strong understanding of cloud-native data engineering practices.
• Google Cloud Platform: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions, Cloud Composer (Airflow), Cloud Storage, Cloud SQL, IAM, Cloud Monitoring, Cloud Logging
• Programming & Data Engineering: Python, SQL, Bash/Shell Scripting, ETL/ELT, Data Warehousing, Data Lake / Lakehouse Architectures, Batch Processing, Real-Time Streaming Architectures

Nice To Haves

• Experience with Vertex AI and Google AI services.
• Experience building AI/ML data platforms and pipelines.
• Knowledge of Large Language Models (LLMs) and GenAI concepts.
• Experience with Gemini models, Agentic AI frameworks, Prompt Engineering, RAG architectures, and Vector Search.
• Experience with Dataproc, Spark, or PySpark.
• Familiarity with event-driven architectures.
• Experience with Terraform or Infrastructure as Code.
• Understanding of cloud cost optimization and FinOps practices.
• Financial Services industry experience.
• Google Cloud Professional Data Engineer Certification.

Responsibilities

• Design, develop, and optimize ETL/ELT pipelines for structured and unstructured data.
• Build scalable batch and streaming data processing solutions using GCP technologies.
• Develop event-driven data processing solutions leveraging Pub/Sub and Cloud Functions.
• Create and maintain data ingestion frameworks for enterprise data platforms.
• Design and optimize data lake, lakehouse, and data warehouse solutions.
• Build efficient data models supporting analytics, reporting, and AI/ML workloads.
• Optimize performance, scalability, and cost efficiency of data pipelines and queries.
• Develop robust Python-based solutions and frameworks.
• Automate orchestration and workflow management using Cloud Composer (Airflow).
• Implement CI/CD pipelines and deployment automation.
• Apply software engineering best practices for testing, monitoring, and observability.
• Partner with business stakeholders, analytics teams, data scientists, and engineers to deliver data solutions.
• Troubleshoot production issues and perform root cause analysis.
• Continuously improve reliability, scalability, security, and operational excellence.

Benefits

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs
• Other benefits as provided by local policy and eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed