Principal Data Engineer

Shaw Daniels Solutions; Birmingham; On-site; GBP 85,000 - 120,000; Full time

Job summary

A global tech solutions company is seeking a Principal Data Engineer in Birmingham. This role involves shaping the architecture and scalability of the enterprise data platform. Key responsibilities include leading design, defining technical strategy, and mentoring engineers. Candidates should have extensive experience with cloud-based data platforms, strong leadership skills, and exceptional communication abilities. This exciting opportunity allows significant autonomy in technical decision-making and collaboration across teams.

Qualifications

• Extensive experience designing and operating large-scale, cloud-based data platforms.
• Strong architectural judgement, balancing technical excellence with business outcomes.
• Proven leadership and influence across cross-functional teams.

Responsibilities

• Lead the design and evolution of scalable, secure, and reliable data architectures.
• Define and drive standards and best practices across teams.
• Mentor and develop senior data engineers.

Skills

Designing large-scale cloud-based data platforms

Data modelling

Pipeline orchestration

Performance optimisation

Leadership and influence in cross-functional teams

Technical writing and documentation

Business acumen

Tools

Google Cloud Platform (Big Query, Data form, Cloud Composer)

Airflow

Kubernetes

Job description

Principal Data Engineer

Location: United Kingdom

Our Client

They are a global content solutions company, powered by technology and human expertise. They help organisations grow the value of their ideas, data, and content by enabling them to be understood - everywhere.

With over 45 AI patents, industry-leading technology, and expert talent, they support more than 80 of the world’s top 100 brands. Their teams operate across 60+ locations worldwide, delivering solutions that accelerate time-to-market, deepen customer engagement, and unlock new global opportunities.

Role Overview

As Principal Data Engineer, you will be a senior technical leader responsible for shaping the architecture, scalability, and evolution of the enterprise data platform.

This role goes far beyond delivery. You will define technical strategy, design scalable data systems, mentor senior engineers, and partner closely with product, engineering, analytics, and business leaders to transform strategic goals into robust, data-driven solutions.

You will have significant autonomy to influence architectural decisions, introduce best practices, and create a lasting technical legacy across the global data ecosystem.

Key Responsibilities

• Lead the design and evolution of scalable, secure, and reliable data architectures supporting BI, analytics, and ML workloads.
• Define and drive data engineering standards, architecture patterns, and best practices across teams.
• Influence technical strategy across engineering, product, and analytics through clear communication and stakeholder collaboration.
• Anticipate future data needs, balancing long-term vision with pragmatic delivery.
• Own reliability, performance, and observability of critical data systems, including SLO definition and operational resilience.
• Mentor and develop senior data engineers through architecture reviews, technical coaching, and knowledge sharing.
• Champion data quality, governance, monitoring, incident response, and cost optimisation.
• Evaluate emerging tools and technologies, guiding adoption where they deliver genuine business value.

Skills & Experience

• Extensive experience designing and operating large-scale, cloud-based data platforms.
• Deep expertise in data engineering fundamentals: data modelling, pipeline orchestration, distributed systems, and performance optimisation.
• Strong architectural judgement, balancing technical excellence with business outcomes.
• Proven leadership and influence across cross-functional teams.
• Demonstrated success mentoring senior engineers and scaling team effectiveness.
• Exceptional communication skills, including technical writing, documentation, and executive presentations.
• Strong business acumen with the ability to connect technical decisions to measurable ROI.

Desirable Experience

• Hands-on experience with Google Cloud Platform (Big Query, Data form, Cloud Composer).
• Metadata management and data cataloguing (e.g., DataHub, Alation).
• Modern orchestration platforms (Airflow, Prefect, Dagster).
• Cloud-native architectures, including Kubernetes, serverless, and Infrastructure as Code.
• Data mesh or decentralised data architecture implementations.
• Model Context Protocol (MCP) for data assets.
• Open-source contributions or active participation in the data engineering community.