InTune Mobile Engineer

Bromley

9 months ago

Applications closed

Role: InTune Mobile Engineer

Location: Bromley, 3 days per week on site required

Duration: 12-month contract

Rate: £650.00 - £700.00 per day through umbrella

As part of the Corporate Mobile team, you'll help define and evolve our mobile strategy-engineering secure, scalable, and intuitive mobile solutions for our global workforce. You'll take a hands-on role in both enhancing existing mobile services and driving new initiatives, while ensuring compliance with architectural and security standards.

This isn't just a support role-it's an opportunity to lead engineering change, create meaningful impact, and be part of a talented team dedicated to automation, innovation, and world-class employee experience.

What You'll Be Doing

Engineer and configure enterprise mobile solutions using modern platforms like Microsoft Intune
Champion automation-first practices to enhance user experience and reduce manual overhead
Collaborate with teams across Security, Product, Engineering, and Architecture to deliver robust and secure mobile platforms
Own the design and delivery of high- and low-level technical solutions
Contribute to the development backlog and feature releases, ensuring accuracy in technical documentation
Manage technical artefacts, design documentation, and support operating model creation
Deliver new services and support ongoing BAU activities with strategic thinking

What You'll Bring

Expertise in Microsoft Intune engineering, including reporting, workflow automation, and vulnerability management
Working knowledge of other MDM platforms such as BlackBerry UEM or Workspace ONE
Solid experience with Apple Business Manager, Android Enterprise, KNOX, and Google Zero Touch
Scripting skills in PowerShell, Python, or similar for automation
Familiarity with Mobile Threat Defence (e.g., Microsoft Defender for Endpoint)
Experience with Microsoft SQL and reporting tools
Understanding of Cloud technologies (Azure / AWS) and how they support mobile infrastructure
ITIL knowledge and an appreciation for structured service management practices

Why Join Us?

Work in a global, collaborative environment where innovation is encouraged
Make a real impact by supporting mission-critical platforms used by tens of thousands daily
Be part of a dynamic team that values quality, security, and performance
Access to excellent training, support, and development opportunities

Candidates will ideally show evidence of the above in their CV to be considered please click the "apply" button.

Please be advised if you haven't heard from us within 48 hours then unfortunately your application has not been successful on this occasion, we may however keep your details on file for any suitable future vacancies and contact you accordingly.

Pontoon is an employment consultancy. We put expertise, energy, and enthusiasm into improving everyone's chance of being part of the workplace. We respect and appreciate people of all ethnicities, generations, religious beliefs, sexual orientations, gender identities, and more. We do this by showcasing their talents, skills, and unique experience in an inclusive environment that helps them thrive

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

Industry Insights

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

Jan 18, 2026

Jobs Careers

Data Engineering Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data engineering in your 30s, 40s or 50s? You’re not alone. In the UK, companies of all sizes — from fintechs to government agencies, retailers to healthcare providers — are building data teams to turn vast amounts of information into insight and value. That means demand for data engineering talent remains strong, but there’s a gap between media hype and the real pathways available to mid-career professionals. This guide gives you the straight UK reality check: which data engineering roles are genuinely open to career switchers, what skills employers actually look for, how long retraining really takes and how to position your experience for success.

Jan 13, 2026

Jobs

How to Write a Data Engineering Job Ad That Attracts the Right People

Data engineering is the backbone of modern data-driven organisations. From analytics and machine learning to business intelligence and real-time platforms, data engineers build the pipelines, platforms and infrastructure that make data usable at scale. Yet many employers struggle to attract the right data engineering candidates. Job adverts often generate high application volumes, but few applicants have the practical skills needed to build and maintain production-grade data systems. At the same time, experienced data engineers skip over adverts that feel vague, unrealistic or misaligned with real-world data engineering work. In most cases, the issue is not a shortage of talent — it is the quality and clarity of the job advert. Data engineers are pragmatic, technically rigorous and highly selective. A poorly written job ad signals immature data practices and unclear expectations. A well-written one signals strong engineering culture and serious intent. This guide explains how to write a data engineering job ad that attracts the right people, improves applicant quality and positions your organisation as a credible data employer.

Jan 6, 2026

Education Jobs

Maths for Data Engineering Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data engineering jobs in the UK, maths can feel like a vague requirement hiding behind phrases like “strong analytical skills”, “performance mindset” or “ability to reason about systems”. Most of the time, hiring managers are not looking for advanced theory. They want confidence with the handful of maths topics that show up in real pipelines: Rates, units & estimation (throughput, cost, latency, storage growth) Statistics for data quality & observability (distributions, percentiles, outliers, variance) Probability for streaming, sampling & approximate results (sketches like HyperLogLog++ & the logic behind false positives) Discrete maths for DAGs, partitioning & systems thinking (graphs, complexity, hashing) Optimisation intuition for SQL plans & Spark performance (joins, shuffles, partition strategy, “what is the bottleneck”) This article is written for UK job seekers targeting roles like Data Engineer, Analytics Engineer, Platform Data Engineer, Data Warehouse Engineer, Streaming Data Engineer or DataOps Engineer.