C# Developer

Cititec Talent
1 year ago
Applications closed

Related Jobs

View all jobs

Data Scientist (Government)

Data Engineer Data Modeling

Data Analyst - Power BI Specialist

MLOps Engineer

Data Engineer - Configuration

Data Analyst - Power BI Specialist

C#/.NET Developer

Commodities & Data Analytics

UK (remote)


Our client is a global provider of data and analytics for the commodities markets, and they are seeking a skilled C#/.NET Developer with a strong background in data-driven applications and commodities markets. The successful candidate will be responsible for building and maintaining software solutions that enable accurate, timely, and actionable insights to its customers. This role requires a deep understanding of both software development and the data-intensive needs of the commodities industry.


Key Responsibilities:

  • Design, develop, and maintain high-performance software applications using C#/.NET technologies.
  • Collaborate with cross-functional teams (data engineers, analysts, and product managers) to build robust, scalable systems that process large datasets efficiently.
  • Work with real-time and historical data related to commodities markets (e.g., metals, energy, agriculture, etc.) to deliver high-quality analytics and insights to end users.
  • Optimize and enhance existing systems, ensuring they meet the performance and scalability requirements for data-heavy applications.
  • Develop API services to integrate with internal and external platforms, ensuring smooth data flow and real-time data delivery.


Required Qualifications:

  • 5+ years of experience in software development using C#/.NET technologies.
  • Knowledge of commodities markets (e.g., metals, agriculture, energy).
  • Strong understanding of data structures, algorithms, and design patterns.
  • Experience working with large datasets and developing data-intensive applications.


  • Experience with SQL or other relational databases, as well as working with NoSQL databases.
  • Solid experience with RESTful APIs and web services.
  • Familiarity with cloud platforms such as Azure for deploying and managing applications.


Preferred Qualifications:

  • Experience with Big Data technologies (e.g., Hadoop, Spark) or data streaming platforms (e.g., Kafka).
  • Knowledge of data analytics tools and platforms used within the commodities industry.
  • Experience in building real-time data processing systems.

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 Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 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.