Data Consultant (Data, AI, ML)

Data Engineer (hiring mid to senior levels | 2yrs+)

Newcastle (on-site)

£50,000-£100,000 + bonus

Data Engineer Overview

A growing high-calibre tech consultancy is seeking Data Engineers of various levels and disciplines to build robust, scalable data platforms/implement AI/ML for clients.

They're a joint venture between two global leaders in consulting and investment management, and rather than hiring for a single technology stack or narrow role, they're assembling a team of exceptionally smart engineers, data specialists and technical leaders who can solve difficult problems, communicate well, and thrive in highly demanding environments.

They're building teams in data, AI/ML, and technical leadership, with a particular focus on hiring exceptionally strong problem solvers rather than simply matching a specific tech stack. They're looking for people who understand how things work under the hood, not just how to use the latest tools.

The environment is geared towards people who enjoy tackling complex challenges, working closely with end users, and taking ownership from day one. Most of the work is greenfield, with separate divisions in financial services and defence -related projects, and will be creating insurance and energy divisions in the near future.

They’re hiring for, and value, Data Engineers who:

Enjoy working on challenging systems
Are friendly
Truly understand problem-solving principles
Enjoy variety
Are adaptable and articulate

Data Engineer Role

You will design and maintain data pipelines and systems that support analytics and operational use cases.

Data Engineer Responsibilities include:

Building data pipelines and data-intensive applications
Developing in Python and SQL
Working with distributed systems (e.g. Spark, Databricks)
Managing data orchestration (e.g. Airflow)
Ensuring data quality, reliability, and performance

Data Engineer cross over with AI/ML could include:

Integrating AI components into applications and workflows
LLM evaluation, failure modes, and mitigation strategies
Testing and debugging non-deterministic systems
RAG
Understanding of the risks and limitations of AI and where statistical models or deterministic logic would be more appropriate
LLM principles and transformer architectures
LLM performance evaluation and inference optimisations
Developing modules for edge, constrained or air-gapped environments would be a plus
Explainable AI or AI safety/security would be a plus

Data Engineer Additional Criteria:

STEM Degree from a leading university (2:1 or above)
Eligibility for UK SC-level security clearance
Experience in defence or highly regulated environments is advantageous, but not required

Data Engineer Benefits: