Data Engineer
About The Position
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world. We are seeking a highly skilled GCP Data Engineer with strong Python expertise to design, build, and optimize scalable data solutions on Google Cloud Platform (GCP). The ideal candidate will have hands-on experience developing batch and real-time data pipelines, working with large-scale datasets, and enabling analytics and AI/ML use cases.
Requirements
- GCP Services: BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Functions (Gen2), Cloud Composer (Airflow), Cloud Storage, Cloud SQL
- Programming: Python (advanced)
- Query Language: SQL (advanced)
- Data Processing: Batch & Streaming architectures
- Scripting: Bash/Shell scripting
- Concepts: Data Warehousing, ETL/ELT, Data Lake / Lakehouse architectures
- Insurance Domain Experience|Certification Preferred
- Google Cloud Platform (GCP)o Vertex AIo Cloud Runo BigQueryo Cloud Storageo IAMo Cloud Loggingo Cloud Monitoring
- AI & Machine Learningo Large Language Models (LLMs)o Gemini Modelso Agentic AI Frameworkso Prompt Engineeringo RAG Architectureso Vector Search Conceptso Semantic Retrievalo AI Evaluation Frameworks
- Data & Analyticso SQLo BigQueryo Metadata Modelingo Data Pipelines
- 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)
Nice To Haves
- Experience with Dataproc (Spark/PySpark) for large-scale processing
- Familiarity with event-driven architectures
- Knowledge of Terraform or Infrastructure as Code
- Understanding of cost optimization (FinOps)
- Google Cloud Professional Data Engineer Certification
- Experience supporting AI/ML data pipelines
Responsibilities
- Develop and optimize ETL/ELT workflows for structured and unstructured data processing using GCP services such as Dataflow, Dataproc, and Pub/Sub
- 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 machine learning workloads
- Optimize performance and cost of data pipelines and queries
- Develop solutions using Python
- Automate workflows and orchestration using Cloud Composer (Airflow)
- Implement CI/CD pipelines and deployment automation
- Collaborate with analytics, AI/ML, and business teams for data consumption needs
- Troubleshoot data issues and perform root cause analysis
- Continuously improve pipeline reliability, scalability, and performance
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
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
