Principal Data Engineer (Cloud)

TL;DR

Principal Data Engineer (Cloud): Designing and implementing enterprise-scale cloud data platforms and architectures with an accent on scalable data pipelines and DataOps standards. Focus on driving the adoption of modern cloud technologies, optimizing platform performance, and establishing engineering excellence across the organization.

Location: Hybrid/Remote (Must be based in the UK and hold SC Clearance)

Salary: £300 – £1000 per day

Company

A leading organisation undergoing a significant digital transformation focused on enhancing its enterprise data platform and analytics capabilities.

What you will do

• Design and implement enterprise-scale cloud data platforms and architectures.
• Lead the development of scalable data pipelines, integration frameworks, and reusable data products.
• Drive best practices across Data Engineering, DataOps, and DevOps.
• Implement CI/CD pipelines, Infrastructure as Code, and automated deployment processes.
• Ensure data quality, governance, security, and compliance across enterprise platforms.
• Mentor Data Engineers and provide technical leadership to the wider engineering function.

Requirements

• 7+ years of experience in Data Engineering, Data Platform Development, or Software Engineering.
• Must possess SC Clearance.
• Expertise with cloud platforms such as Microsoft Azure, AWS, or Google Cloud.
• Advanced SQL and Python development skills.
• Experience building ETL/ELT pipelines and modern data integration solutions.
• Strong understanding of DataOps, DevOps, CI/CD, and Infrastructure as Code.

Nice to have

• Cloud certifications (Azure, AWS, or GCP).
• TOGAF, DAMA CDMP, or Data Engineering certifications.
• Experience with AI/ML platforms, MLOps, or Data Mesh/Fabric architectures.
• Experience within Aerospace, Defence, or Manufacturing industries.

Culture & Benefits

• Competitive salary and flexible working options.
• Opportunity to shape enterprise-wide data strategy and architecture.
• Access to cutting-edge cloud technologies including Azure, Microsoft Fabric, Databricks, and Snowflake.
• Technical leadership role with significant influence.
• Ongoing professional development and certification opportunities.

Hiring process

• Multi-stage interview process.
• Technical and competency-based assessments.