Head of DevOps and DataOps

Leicester
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Lead Data Architect | Snowflake & AWS | £130k | Roadmap to Head of Engineering

Data Engineer

Lead Data Engineer

Lead Data/Head of Data Engineer

Data Engineer (18 Months FTC)

Salary £59,966 - £67,468, 33 days annual leave plus bank holidays, hybrid working (3 days per week in office), competitive pension and other benefits

Hays Technology are working in partnership with a Higher Education client to recruit a Head of DevOps and DataOps vacancy on a permanent basis.

It is an exciting time to be joining this Digital Services team as they deliver on an ambitious digital strategy and masterplan that will drive significant digital transformation across the organisation. The role is responsible for the development and support of the major applications, master data, and information reporting systems that support the University's business processes, including student records, timetabling, accommodation management, research management, finance, HR/payroll, marketing, and facilities management. It is critical to enabling the University to streamline and automate processes to enhance efficiency and reliability; ensuring valuable data and insights are provided to support the University's growth, serve students, and improve operational efficiency.

You will have responsibility for a team of 23 staff within the department, including line management for the team leaders of the five sub teams; DevOps, DataOps, ERPOps, Dev Team, Agile Delivery.

Key Responsibilities:

Leadership & Strategy

Lead and develop multidisciplinary teams including solution, low‑code, data and integration developers, delivering new digital solutions, automation and operational excellence.
Set future technology direction through horizon planning, guidance on emerging platforms (e.g. Power Platform and data technologies) and adoption of best practice.
Embed strong customer focus, continuous learning, coaching, and knowledge‑sharing to maximise capability and minimise operational risk.Technical Governance & Quality

Establish and maintain development standards, toolsets, source control, documentation templates and policies.
Ensure quality, security and resilience are integral to all development and integration activities.
Maintain expert knowledge of systems integration, solution development and emerging trends, acting as a trusted technical adviser to senior stakeholders.
Participate as a key member of the Architecture Board, assuring solution design and architectural compliance.Systems Ownership & Operations

Own and continuously improve critical enterprise systems (e.g. ERP, Student Records and associated data, application and database platforms).
Act as escalation point for 2nd and 3rd line incidents, ensuring timely resolution and supplier engagement.
Lead preventative maintenance, upgrades, disaster recovery planning, configuration management and risk management for relevant systems.
Work closely with partners and suppliers on roadmap development, defects, enhancements and incident resolution.Resource & Delivery Management

Plan and prioritise resources across Dev, Agile Delivery, ERPOps and DataOps teams, balancing operational demands with long‑term strategy.
Maintain accurate resource plans and guide estimation and sizing of development activity.
Work with Service Owners and Project Managers to ensure effective allocation of developer capacity for projects, change, support and upgrades.
Proactively identify, mitigate and resolve resourcing risks to maintain delivery momentum.If you would like to apply, you must have the following skills and experience:

Educated to degree level in an IT related discipline or with equivalent additional experience.
Previous experience in an IT Leadership or management role.
Substantial technical experience in solutions development and system implementation within one or more operating environments within a complex IT service serving a large organisation.
Brings clear, 'customer focussed' thinking to the development of technical strategies, standards and design principles.
Maintains excellent awareness of technical innovations and emerging trends.
Successful track record in building and leading highly flexible teams of developers and technical experts, operating in a matrix environment.
Familiar with the technologies relevant to the team's purpose.
Experience with any or all of the following are of interest: Microsoft M365 and Azure technologies, including Office 365, Business Intelligence or SAP ERP (Basis, FI, HR, ESS/MSS, Payroll, SRM, PI) or Tribal SITS or MS SQL Server.If you have the relevant experience and would like to apply, please submit your CV.

Hays Specialist Recruitment Limited acts as an employment agency for permanent recruitment and employment business for the supply of temporary workers. By applying for this job you accept the T&C's, Privacy Policy and Disclaimers which can be found at (url removed)

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.

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

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

The Skills Gap in Data Engineering Jobs: What Universities Aren’t Teaching

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.