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

Apply Now

IAM Specialist

Royal Leamington Spa
8 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst / Data Scientist

Data Engineer - Burton-On-Trent...

E-Commerce Data Analyst

Data Engineer

AWS Data Engineer

AWS Data Engineer

Position: IAM Specialist
Location: Leamington Spa/Gaydon, UK
Salary: £60,000

About the Role
As an IAM Specialist, you will be accountable for the development and ongoing management of IAM policies and procedures. Your role will involve identifying and mitigating IAM-related risks throughout the business, ensuring that all risks are assessed and addressed proactively. You will deliver comprehensive identity and access management services as part of the IAM Specialist team.

Key Responsibilities:

Provide expert consultancy on IAM best practices (technical, governance, and process) to various teams and stakeholders.
Take full responsibility for the creation and maintenance of IAM policies and procedures, ensuring they cover all aspects of identity and access management.
Deliver IAM services through the selected software and service partners.
Continuously enhance the IAM processes to drive business efficiency.
Provide detailed data analytics to track and report key IAM metrics, using this data and audit procedures to ensure least privilege access and prevent toxic access.
Identify IAM-related risks and take proactive steps to assess, mitigate, and resolve these risks across the business.
Engage with and communicate IAM policies and procedures effectively to stakeholders across the organization.
Act as the escalation point for any IAM-related alerts or issues, raised either by other departments or monitoring systems.
Stay current with trends in information security, proposing proactive mitigations as necessary.
Your Profile

Essential skills/knowledge/experience:

Extensive experience as a subject matter expert in Identity and Access Management, with deep technical knowledge in Microsoft environments (Windows OS, Active Directory), Linux-based systems (desktop and server), and core infrastructure (networking, databases).
Strong understanding of IAM governance principles and industry best practices.
Experience managing information security risks related to identity.
Familiarity with SAML/OAUTH protocols.
Proven track record of working cross-functionally and managing relationships with external agencies.
Sound understanding of IT compliance standards, particularly in design and implementation.
Experience managing senior stakeholder relationships.
Strong IT skills, with the ability to analyze data for reporting and follow detailed work instructions.
Relevant degree or equivalent experience is preferred.

Desirable skills/knowledge/experience:

Knowledge of IAM in a DevOps environment, including API management platforms, containerization, and cloud platforms (Google Cloud, Azure, AWS).
Familiarity with information security auditing techniques.
Experience managing information security in operational technology environments (e.g., PLCs, embedded systems in industrial machinery).
Experience in managing information security within a manufacturing organization.
Understanding of business areas such as suppliers and retailers, and how their systems interact.
If this could be the ideal role for you, please apply with an up-to-date CV to be considered.

In Technology Group Ltd is acting as an Employment Agency in relation to this vacancy

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

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

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.