Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Science Analytics and Reporting Specialist

Reading
6 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Business Intelligence Analyst (Power BI / SQL / DAX)

Data Engineer

Science Analytics and Reporting Specialist

Location: RG7 4PR, located between Reading and Basingstoke, with free onsite parking.

Package: £47,860 - £70,200 (depending on your suitability, qualifications, and level of experience)

Working pattern: AWE operates a 9-day working fortnight. We will consider flexible working requests so that your work may fit in with your lifestyle. Just let us know your preferred working pattern on your application.

Let us introduce the role

The Science Business Operations team at AWE is committed to driving excellence and innovation in our business processes. We are seeking a motivated individual with a growth mindset to join us as a Science Analytics & Reporting Specialist. This role offers the opportunity to make a significant impact on our reporting and analytics capabilities, supporting key stakeholders in making informed business decisions.

As a Science Analytics & Reporting Specialist, you will collaborate closely with all Science areas to develop delivery performance indicators and ensure effective reporting across all levels of the business. You will coordinate the development and management of reporting and metrics across various aspects of our business operations, including resourcing, finances, and delivery. This role requires regular engagement with stakeholders both within science and across the broader business.

Who are we looking for?

We do need you to have the following:

Proficiency in Microsoft products including Power Automate and PowerApps.

Understanding and experience in data engineering, encompassing ETL processes, data quality, integrity, and security.

Experience with reporting tools such as Power BI.

Experience with EPBVS (Enterprise Planning & Budgetary Cloud Service).

Strong proficiency in SQL and other data querying languages.

Proven analytical and critical thinking skills, with the ability to interpret complex data and present findings to a diverse audience

Everyone who works at AWE brings unique skills and perspectives to the table. We recognise that great people don't always 'tick every box'. That's why we focus on your potential, your fit with our values, your transferable skills as well as your experience. Even if you don't meet every point below, but you feel that this role and AWE are a great fit for you, please go ahead and apply, we'd love to receive your application.

Whilst not to be considered a tick list, we'd like you to have experience in some of the following:

Managing a diverse range of stakeholders, including senior leadership/stakeholders as customers

Growth mindset with a proactive approach to seeking opportunities for continuous improvement and efficiencies

Excellent written and verbal communication skills, with the ability to present complex information clearly and concisely to various audiences.

Understanding and experience with Data Science, including development and implementation of advanced analytics models, such as machine learning and statistical models

Knowledge of Palantir Foundry and its data integration and analytics capabilities

Understanding of how to present metrics and management information

Project management experience, with the ability to manage multiple projects and deadlines simultaneously

Some reasons we think you'll love it here:

AWE has wide range of benefits to suit you. These include:

9-day working fortnight - meaning you get every other Friday off work, in addition to 270 hours of annual leave.

Market leading contributory pension scheme (we will pay between 9% and 13% of your pensionable pay depending on your contributions).

Family friendly policies: Maternity Leave - 39 Weeks Full Pay and Paternity Leave - 4 Weeks Full Pay.

Opportunities for Professional Career Development including funding for annual membership of a relevant professional body.

Employee Assistance Programme and Occupational Health Services.

Life Assurance (4 x annual salary).

Discounts - access to savings on a wide range of everyday spending.

Special Leave Policy including paid time off for volunteering, public service (including reserve forces) and caring.

The 'Working at AWE' page on our website is where you can find full details in the 'AWE Benefits Guide'.

Important things you need to know:

You will need to obtain and maintain the necessary security clearance for the role. This will be funded by AWE. The nature of our work does mean you need to be a British Citizen who has been resident in the UK for the past 5 years in order to apply for SC clearance and 10 years for DV.

We want you to feel comfortable and able to shine during our recruitment process. Please let us know on your application form if you need any adjustments/accommodations during the process.

Our interviews typically take place over Teams and for most roles are a 1 stage process.

IF HYBRID POSSIBLE:

Hybrid working is available for this role on an informal, non-contractual basis. Typically 2 days onsite per week.

#LI-DS

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Engineering Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data engineering hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise reliable pipelines, modern lakehouse/streaming stacks, data contracts & governance, observability, performance/cost discipline & measurable business outcomes. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for platform‑oriented DEs, analytics engineers, streaming specialists, data reliability engineers, DEs supporting AI/ML platforms & data product managers. Who this is for: Data engineers, analytics engineers, streaming engineers, data reliability/SRE, data platform engineers, data product owners, ML/feature‑store engineers & SQL/ELT specialists targeting roles in the UK.

Why Data Engineering Careers in the UK Are Becoming More Multidisciplinary

For many years, data engineering in the UK meant designing pipelines, moving data between systems, and ensuring analysts had what they needed. Today, the field is expanding. With cloud platforms, machine learning, real-time analytics and the explosion of sensitive personal data, employers expect data engineers to do much more. Modern data engineering is no longer just about code and storage. It requires legal awareness, ethical judgement, psychological insight, linguistic clarity and human-centred design. These disciplines shape how data is collected, processed, explained and trusted. In this article, we’ll explore why data engineering careers in the UK are becoming more multidisciplinary, how law, ethics, psychology, linguistics & design now influence job descriptions, and what job-seekers & employers must do to thrive.

Data Engineering Team Structures Explained: Who Does What in a Modern Data Engineering Department

Data has become the lifeblood of modern organisations. Every sector in the UK—finance, healthcare, retail, government, technology—is increasingly relying on insights derived from data to drive decisions, deliver products, and improve operations. But raw data on its own isn’t enough. To make data useful, reliable, secure, and scalable, companies must build strong data engineering teams. If you’re recruiting for data engineering or seeking a role, understanding the structure of such a team and who does what is essential. This article breaks down the typical roles in a modern data engineering department, how they collaborate, required skills and qualifications, expected UK salaries, common challenges, and advice on structuring and growing a data engineering team.