Senior OSS Data Architect: Hybrid Cloud & Data Integration

Capgemini Engineering; Newbury; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Digital learning platforms

Disability Confident Employer

Job summary

Capgemini Engineering is seeking an OSS Data Architect to act as senior technical authority for end-to-end data extraction, connectivity and ingestion architecture, defining strategy and standardized patterns for integrating OSS with the Cloud Platform (GCP preferred).

You will lead architectural design, governance, security, and stakeholder engagement, promoting reusable patterns and DataOps across large teams while ensuring compliance and performance.

Qualifications

• 12-15+ years in data architecture with 8-10+ years in data integration, ETL/ELT and data warehousing in large enterprises.
• Proven data integration design experience for OSS domains (Inventory, Performance, Fault, Provisioning, Ticketing).
• Expert-level knowledge of data ingestion patterns: batch, API, JDBC, and real-time streaming (CDC, Kafka).
• Deep understanding of hybrid cloud connectivity and security (VPNs, interconnects, firewalls, API security).
• Ability to create and govern reusable architectural patterns and standards for large teams.

Responsibilities

• Architectural Strategy & Design
• Technical Governance & Standards
• Stakeholder Management & Technical Leadership
• Security & Compliance

Skills

Data architecture

Data integration

ETL/ELT

Data warehousing

OSS systems

API integration

Real-time streaming

Hybrid cloud security

GCP (BigQuery)

Terraform

CI/CD DataOps

Tools

Kafka

BigQuery

Terraform

Apigee

Job description

Capgemini Engineering is seeking an OSS Data Architect to act as senior technical authority for end-to-end data extraction, connectivity and ingestion architecture, defining strategy and standardized patterns for integrating OSS with the Cloud Platform (GCP preferred).

You will lead architectural design, governance, security, and stakeholder engagement, promoting reusable patterns and DataOps across large teams while ensuring compliance and performance.