Senior Data Extraction Engineer

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.
Your Role
As a Senior Data Engineer – Google Cloud Platform at Capgemini, you will play a key role in building and evolving enterprise-scale data platforms that power analytics, reporting, AI, and business-critical data products. You will combine strategic architecture thinking with hands-on engineering expertise to design, build, deploy, and support production-grade data solutions on Google Cloud Platform (GCP).
You will own data pipelines end-to-end, from initial architecture and design through implementation, deployment, monitoring, and operational support. Working closely with Product Owners, Data Architects, Business Stakeholders, and Engineering teams, you will help establish scalable data foundations that enable trusted and accessible enterprise data.
This role requires a builder mentality, strong cloud expertise, and a passion for transforming both structured and unstructured data into valuable business assets.
Responsibilities & Scope
Cloud Data Architecture & Platform Design
Design end-to-end data platform architectures supporting data ingestion, transformation, storage, and consumption.
Define scalable, maintainable, and cost-effective cloud data solutions leveraging Google Cloud Platform services.
Establish reusable architecture patterns, standards, and best practices across the data ecosystem.
Evaluate and select appropriate technologies and architectural approaches for:
Batch Processing
Stream Processing
Event-Driven Architectures
Structured Data Workloads
Unstructured Data Workloads
Translate business and operational requirements into scalable technical solutions.
Data Pipeline Engineering
Design, develop, deploy, and support enterprise-grade data pipelines.
Build ingestion frameworks for enterprise source systems including:
Oracle
CRM Platforms
Internal Business Applications
Engineering Systems
Develop ELT and ETL processes that support enterprise analytics and operational data requirements.
Implement data quality validation, reconciliation, and monitoring capabilities.
Support production operations and continuously optimize pipeline performance.
Google Cloud Platform Engineering
Design and implement solutions using:
BigQuery
Cloud Storage (GCS)
Dataflow
Apache Beam
Pub/Sub
Cloud Composer (Airflow)
Cloud Functions
Cloud Run
Vertex AI
Manage data storage architecture, lifecycle policies, security controls, and cloud resource optimization.
Implement Infrastructure-as-Code (IaC) and deployment automation practices.
Contribute to cloud governance, reliability, scalability, and operational excellence.
AI & Unstructured Data Processing
Develop processing pipelines for unstructured and multimodal data including:
PDF Documents
Excel Files
PowerPoint Presentations