C# Developer

Preston

9 months ago

Applications closed

Related Jobs

View all jobs

Senior SQL Developer

Data Engineer - Configuration

Data Engineering Product Owner, Technology, Data Bricks, Microsoft

Data Engineer - SC Cleared

Senior Data Engineer (Big Data/ Hadoop/ Spark) (Banking)

Lead Data Engineer

C# Developer – Software Developer – Preston
Keywords: C#, .Net, ASP.Net, SQL Server, HTML, JavaScript, MVC, TDD, Agile, Scrum
Location: Preston, Lancashire - commute from Chorley, Blackpool, Blackburn

Join a forward-thinking software development team in Preston, Lancashire as a C# Developer, contributing to a suite of innovative products in a dynamic Agile/Scrum environment. This is a fantastic opportunity to grow your career within a well-established company offering a clearly defined progression path and a competitive benefits package.
About the Role:
As a C# Software Developer, you'll play a key role in the full software development lifecycle, from initial design and architecture through to implementation and delivery. Working within a collaborative Agile team, you'll contribute to building scalable, maintainable solutions using the latest technologies.

Key Responsibilities:
Develop and maintain applications using C# and ASP.Net Core
Build and consume RESTful services
Work collaboratively in Agile/Scrum teams
Ensure adherence to established coding standards
Contribute to continuous improvement of software development processesRequired Skills & Experience:
Commercial experience in C# and .Net development
Strong knowledge of SQL Server
Experience with ASP.Net Core and RESTful APIs
Exposure to Angular and/or WPF
Familiarity with Azure-based development and deployment
Degree in Computer Science or a related field (or equivalent experience)
Proven ability to work through the full software development lifecycle in an Agile environmentWhy Apply? This is an excellent opportunity for a C# Developer ready to take the next step in their career. You’ll be part of a supportive team that encourages innovation and career growth. The company is actively hiring, so early applications are encouraged.
Apply now by sending your CV to Alex Palmer – interviews are being scheduled immediately.

C# Developer - Preston, Chorley, Blackpool, Blackburn - .Net Core, Azure, Angular, Software developer

Contact – Alex Palmer

If you have not heard back from us within 5 working days, please assume that your application has been unsuccessful on this occasion. Your profile may be considered for other suitable vacancies that arise within the next 12 weeks.

Erin Associates welcomes applications from people of all ethnicities, genders, sexual orientations, and disabilities. Please inform us if you require any reasonable adjustments at any stage of the application process

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.

Feb 10, 2026

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.

Feb 3, 2026

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.

Jan 23, 2026

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.