Data Engineer

• Location: Newcastle upon Tyne
• Security clearance: must be eligible for UK SC-level security clearance (UK national)
• Visa sponsorship: we are not able to sponsor visas for this role
• Closing date: applications reviewed on a rolling basis

About Neptune North

Neptune North is a high-performing technical consultancy. We build data, AI and software solutions for clients in defence, financial services and private capital, working on demanding problems in challenging environments.

We were founded in 2024 as a joint venture between Oliver Wyman and Rokos Capital Management. We’re headquartered in the centre of Newcastle upon Tyne, with a growing international footprint, and we’re recruiting exceptional engineers across every level.

The role

We’re looking for Data Engineers to build the data foundations that our defence work depends on. This is a hands-on engineering role where you will have impact across a wide variety of projects.

Potential projects might include fully engineered production pipelines, Proof of Concepts (POCs), and applied work to make sensitive or hard-to-reach data usable in operational settings.

Responsibilities

• Design and build data-intensive applications and pipelines, from ingest through to consumption
• Test, troubleshoot and improve data products, ensuring reliability and quality
• Provide technical expertise when it is required within the organisation and in client engagements
• Demonstrate flexibility in taking on work aligned to evolving company priorities
• Play an active role in sharing expertise to raise and re-use capability

What makes a great candidate

You don't need to meet every requirement to apply. If this role excites you, we'd like to hear from you.

Data Engineer:

• Experience designing and building data intensive applications and pipelines
• Strong SQL skills and comfortable working with large, complex datasets
• Experience with distributed computing, cloud platforms and orchestration tools, such as Spark, Databricks, AWS, Azure, GCP or Airflow
• Skill in preparing and cleaning messy data, including feature engineering for machine learning
• A practical approach to keeping pipelines reliable and the data they produce trustworthy
• Experience designing how data is modelled and stored so that others can use it effectively
• Ability to work with analysts, scientists and engineers to understand what they need from the data