Lead DevOps Engineer

Alderley Edge
10 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

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

Senior Data Engineer

Data Engineer

Data Engineer

Data Engineer

Role: Lead DevOps Engineer
Location: Office near Alderley Edge, Cheshire
Working Arrangements: Hybrid working policy of 2 days per week in the office, which is flexible, but the team go in typically on Tuesdays and Thursdays
Salary: Up to £80k plus benefits, including bonus
You’ve been around the block- you’ve worked in big companies, small ones, and have realised that the people make the place. You don’t mind how big the organisation is, as long as there are good people there who are equally as good at what they do.
On the technical side, you have a deep understanding of how infrastructure and systems fit together, how software engineering and production works, how many different technologies work, and have come to the conclusion that the right tool for the job isn’t always necessarily the new buzzword on the scene, and know enough to be able to make the call on what technology fits your current need. Afterall, technology is a tool to finding a solution!
Next on your to-do list is to find a company that not only values your way of thinking, your skills, experience, and pragmatism, but actively encourages, and gives you opportunities, to impart your wisdom to others and lead the way in your team.
If this sounds like you, you’re in for a treat with this role!
I am working with a lovely company that is about to go through a period of transition, going from being a small company to becoming part of a global organisation due to an acquisition. It’s an exciting time for them- everyone there is jazzed for it!
They are hiring in a number of departments and DevOps is no different. Starting with a Lead DevOps Engineer, this role will see you being in a technical leadership role, providing mentoring and skill development to a very bright, enthusiastic DevOps Engineer, and growing the team with another couple of DevOps Engineers, and doing the same for them.
You will be fully hands-on, using a range of tech, but centring around AWS and Terraform, initially.
Here’s an abbreviated list of tech/skills you’ll use in the role:

  • AWS & GCP and various services, including AWS ECS, EC2, Fargate, Lambda, and GCP Compute Engine, Kubernetes Engine (GKE), Cloud Storage, BigQuery, and IAM.
  • Terraform for IaC
  • Docker
  • Kubernetes
  • Linux (sysadmin including firewalls and hardening)
  • Web Server Config (Apache, Nginx)
  • Database management (MongoDB & MySQL) for high availability and backups
  • Git for version control
  • Programming/Scripting languages like Node/TypeScript, Python
  • Serverless Infrastructure
  • Network design & admin
    There is a planned, company-wide, migration from AWS over to GCP in the next year or so, so any familiarity with GCP would be hugely beneficial for the role and you’ll need to be comfortable in switching cloud providers yourself, to be happy in the role. Due to the acquisition, integration experience would be really handy, too.
    Whilst a tech alignment is necessary, it will always be secondary to culture and values fit: being a self-starter, curious, proactive, upbeat, and engaged team member is very important to them.
    This is an interesting role to get stuck into that will provide you with all the technical problems to solve, that will really use the skills you’ve developed, and that will be as rewarding as it is satisfying.
    If this sounds right up your street, apply now or get in touch to find out more!
    We welcome diverse applicants and are dedicated to treating all applicants with dignity and respect, regardless of background

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.

Careers

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.

Jobs

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.

Education

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.