English Teacher

Cargo Fleet
7 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Are you an English Teacher who believes in the power of words to change lives?
Do you have the resilience, passion, and creativity to engage students who’ve struggled in mainstream education?
Smart Education is currently seeking a dedicated and inspiring English Teacher to join a forward-thinking and nurturing alternative provision in the Middlesbrough area. This unique role offers the opportunity to work with students aged 11–16 who face a variety of challenges, including Social, Emotional and Mental Health (SEMH) needs, attention deficit hyperactivity disorder (ADHD), Moderate Learning Difficulties (MLD), and Behavioural, Emotional and Social Difficulties (BESD).
As an English Teacher in this specialist setting, you'll be more than just an educator—you’ll be a mentor, motivator, and a consistent presence in the lives of young people who need it most. Your lessons won’t just focus on grammar and literature—they’ll build confidence, inspire creativity, and provide students with tools they can use far beyond the classroom.
This is your chance to step into a role where every lesson has the potential to reshape a future. If you're looking for a meaningful teaching opportunity where your efforts can have a direct and lasting impact—this is it. Join a team that values innovation, empathy, and unwavering support for every learner.
Your Role Will Include:
•    Delivering engaging, tailored English lessons that spark curiosity and build confidence
•    Creating a safe, structured, and inclusive learning environment
•    Differentiating content to meet diverse learning needs and abilities
•    Working closely with SENCOs, Teaching Assistants, and pastoral teams to develop individual support strategies
•    Supporting emotional regulation and encouraging positive behaviour
What We’re Looking For:
•    Qualified Teacher Status (QTS/QTLS) or equivalent
•    Experience working with students with additional needs, ideally in an SEN, PRU or alternative provision
•    A patient, creative, and adaptable approach to teaching
•    Excellent classroom and behaviour management skills
•    A valid Enhanced DBS (Child or Child & Adult Workforce), or willingness to obtain one
•    A genuine passion for making English accessible, exciting, and empowering
What You’ll Get in Return:
•    Competitive weekly pay
•    Ongoing CPD and access to free training
•    Holiday pay entitlement
•    A supportive, specialist consultant who understands your needs
•    On-site parking and good transport connections
About Smart Education:
Smart Education is a trusted education recruitment agency, dedicated to connecting passionate educators with meaningful opportunities. We’re proud to be expanding our reach into Middlesbrough, bringing our values of integrity, commitment, and care to every placement.
Ready to Teach English with Purpose?
Apply today and join a school where your teaching has impact beyond the classroom. Be the mentor, the motivator, the difference-maker a young person needs

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.