About the Role

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.

Key Responsibilities

Data Engineering & Pipeline Development

• 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.

Data Storage & Analytics

• 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.

Development & Automation

• 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.

Collaboration & Support

• 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.

Required Qualifications

• 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.

Required Technical Skills

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

Preferred Qualifications

• 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.

Keywords

GCP, Google Cloud Platform, Python, BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions, Cloud Composer, Airflow, SQL, ETL, ELT, Data Engineering, Data Pipelines, Streaming, Batch Processing, Cloud Storage, Cloud SQL, Vertex AI, Gemini, Generative AI, Agentic AI, LLM, RAG, Vector Search, Semantic Search, Spark, PySpark, Terraform, Data Warehouse, Data Lake, Lakehouse, CI/CD, Financial Services

The base compensation range for this role in the posted location is: $115,000 - $145,000/ yearly.

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:

• 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

Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.