Data Engineer

Principle; Greater London; Hybrid; GBP 85,000 - 110,000; Full time

Job summary

Principle in London is recruiting a Data Engineer to join a global technology company, focusing on data infrastructure, analytics and security reporting. This hands-on role emphasizes building end-to-end data pipelines and turning complex datasets into business insights.

You will work on pipelines, logging, dashboards and metrics, with ownership of independent engineering projects. The ideal candidate has 4+ years in Data/Analytics/BI engineering, advanced SQL and hands-on AI coding tools.

Qualifications

• 4+ years of experience in Data Engineering, Analytics Engineering, BI Engineering or closely related role.
• Advanced SQL skills with complex queries, transformations and performance considerations.

Responsibilities

• Design, develop and optimise end-to-end ETL/ELT data pipelines.
• Write complex SQL queries for data extraction, transformation, and performance optimisation.
• Use Python to develop and maintain scalable data processes.
• Build reporting datasets, dashboards and data visualisations to track key business metrics.
• Develop data models and infrastructure to support reliable analytics and reporting.
• Independently deliver engineering projects from design through implementation.

Skills

Advanced SQL

Python

Data pipelines

AI coding tools

Tools

AI coding tools

Job description

• Location: London | Hybrid, 3 days onsite

We are recruiting a Data Engineer to join a leading global technology company in London, supporting a high-impact team focused on data infrastructure, analytics and security-related reporting.

This role is ideal for a hands-on Data Engineer or Analytics Engineer with strong SQL and Python skills, experience building end-to-end data pipelines, and the ability to turn complex datasets into meaningful business insights.

You will work on business-critical projects involving data pipelines, logging infrastructure, dashboards and performance metrics, with the opportunity to take ownership of independent engineering projects.

Key Responsibilities

• Design, develop and optimise end-to-end ETL/ELT data pipelines.
• Write complex SQL queries for data extraction, transformation, troubleshooting and performance optimisation.
• Use Python to develop and maintain scalable data processes.
• Build reporting datasets, dashboards and data visualisations to track key business metrics.
• Develop data models and infrastructure supporting reliable analytics and reporting.
• Use AI-assisted coding tools to improve engineering productivity and problem-solving.
• Investigate data issues, debug pipelines and implement data quality checks.
• Collaborate with cross-functional teams to translate business requirements into effective data solutions.
• Independently deliver engineering projects from design through implementation.
• 4+ years of relevant experience in Data Engineering, Analytics Engineering, BI Engineering or a closely related role.
• Advanced SQL skills, including complex queries, data transformations and query optimisation.
• Experience developing and maintaining production ETL/ELT pipelines.
• Practical experience building dashboards, data visualisations and reporting datasets.
• Hands-on experience using AI coding tools as part of software or data engineering workflows.
• Understanding of data modelling, data quality and analytics infrastructure.
• Ability to troubleshoot technical issues and deliver projects independently.
• Experience with data logging, monitoring or event-based datasets.
• Previous experience within a product-led technology company.
• Experience supporting large-scale reporting and analytics environments.

Why Consider This Opportunity?

• Work on high-visibility data engineering projects within a globally recognised technology environment.
• Gain exposure to critical security and compromise-prevention analytics.
• Work alongside engineering teams actively incorporating AI into development workflows.
• Take ownership of end-to-end engineering projects and contribute directly to business-critical metrics.