Associate Data Fabric Engineer

Overview

In this role you will help design and evolve a data fabric to support automation and AI-based systems in a defence context. You will work with cross-functional teams to enable edge deployments, streaming and batch processing, and governed data workflows. You will implement metadata, lineage, and policy-based security to ensure trusted data across distributed environments. This is a hands-on, technology-forward position in a cutting-edge environment with a focus on reliability, scalability, and security.

Pay / Benefits

• Matched contribution pension scheme with life assurance
• Generous holiday allowance with option to purchase additional days
• Health Cash Plan and Private Medical Insurance
• Employee discount portal including Personal Accident Insurance and Travel Insurance
• Volunteering opportunities and support for the Armed Forces community

Responsibilities

• Design, implement, and evolve event-driven data fabric architectures
• Build workflow automation capabilities for repeatable, governed analyst workflows
• Deliver configurable data integration via curated connectors and standard transformation patterns
• Engineer for DDIL environments to enable edge deployments
• Build streaming ingestion, event pipelines, and batch/stream processing workloads
• Implement metadata, lineage, and catalogue capabilities with policy-based security and governance

Key requirements

• Data/platform engineer experience with distributed systems in production
• Hands-on experience with open-source data integration and streaming technologies
• Experience enabling workflow automation for technical users
• Strong understanding of data modelling fundamentals, data contracts, and schema evolution
• Experience designing for reliability, scalability, and operability
• Strong practical security mindset focused on least privilege and auditability

• Distributed systems in production
• Open-source data integration and streaming technologies
• Workflow automation for technical users
• Data modelling fundamentals, data contracts, and schema evolution
• Reliability, scalability, and operability design
• Security mindset: least privilege and auditability

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