Senior Data Analyst

LHH
Reading
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Analyst

Senior Data Analyst - Marketing

Senior Data Architect

Data Engineer

Senior Systems and Data Analyst (Grade L)

Settlements Data Analyst

Inside IR35 | SC Cleared | Contract | Defence


Role Overview

We are seeking a Principal Data Analyst to join a major defence digital programme, supporting the design and delivery of advanced analytics solutions across multiple workstreams.


This is a senior, hands-on role combining technical leadership, stakeholder engagement, and delivery ownership. You will play a key role in shaping data strategy, improving data governance and quality, and enabling data-driven decision-making across the organisation.


Key Responsibilities

As a Principal Data Analyst, you will:



  • Lead the design and delivery of advanced analytics solutions across multiple projects
  • Oversee the development and maintenance of dashboards, reports, and automated workflows using data warehousing and SQL-based solutions
  • Define and implement data governance, security, privacy, and compliance standards
  • Collaborate with data architects, engineers, and senior business stakeholders to shape data strategies
  • Translate complex datasets into clear, actionable insights for technical and non-technical audiences
  • Lead and mentor analysts, contributing to capability and best-practice development
  • Drive innovation through improved data practices, tooling, and emerging technologies

Core Skills & Experience (Essential)

  • Strong experience across the data lifecycle, including governance, quality, and validation
  • Advanced proficiency with SQL and data warehousing solutions
  • Strong experience with data visualisation tools (Power BI, Tableau)
  • Proven experience working with cloud-based or hybrid data environments
  • Strong understanding of data security, privacy, and ethical considerations
  • Experience gathering and translating requirements into scalable data solutions
  • Ability to plan, manage, and lead work packages within multi-disciplinary teams
  • Experience working in Agile or DevOps environments and contributing to technical strategy
  • Degree in STEM, Data Science, or a related discipline
  • Professional certifications in analytics or data engineering
  • Programming experience using Python
  • Exposure to machine learning techniques or advanced statistical modelling

This is not an exhaustive list. We are keen to hear from candidates who may not meet every requirement but bring a strong attitude and willingness to learn.


What We’re Looking For

  • A senior data professional who can lead, influence, and deliver, not just analyse
  • Someone comfortable operating in a regulated, security-conscious environment
  • Strong communication skills and confidence engaging with senior stakeholders
  • Active SC clearance or clear eligibility is mandatory
  • Contract role – Inside IR35
  • Reading-based with hybrid working
  • Long-term opportunity within a large defence programme

Apply

If you’re a Principal Data Analyst with strong technical depth and leadership experience, we’d like to hear from you.


#J-18808-Ljbffr

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.