Senior Golang Engineer (Ref: 186377)

Title: Senior Golang Engineer (Ref: 186377)

Location: Hybrid (2/3 days in the London office a week)

IR35: Outside

Contract Length: 6 month (potential for extension)

Contact: matthew.makranczy@forsythbarnes.com

We are partnered with an award-winning organisation that combines cutting-edge data science with deep expertise in payments data to support financial institutions in the fight against money laundering and fraud. Their innovative, bespoke services help clients uncover the criminal behaviours behind financial crime.

Requirements:

You are detail oriented and enjoy writing and reviewing code to a high standard with tests to prove it.

• Demonstrable ability to write high quality Python/Golang and SQL in a production context. You are happy to learn new programming languages and frameworks as necessary.
• Experience with large volumes of data and high throughput, low latency solutions built on Kafka and Kubernetes
• You have experience with, and are interested in, contemporary approaches to service design, including the use of containers and container orchestration technologies, streaming data platforms, APIs, and in-memory/NoSQL stores.
• You have experience in resolving different solutions and approaches to problems and can choose between pragmatic and rigorous solutions depending on the situation.
• You are comfortable working in adevops-based software development workflow, including building, testing, and continuous integration/deployment. You are also happy to be evolve along with the development process and contribute to its success.
• You are comfortable communicating with a range of stakeholders, including subject matter experts, data scientists, software engineers, devops and security professionals.
• You have the ability to engage with best practices for code review, version control, and change control, balancing the need for a quality codebase with the unique and particular demands of scale-up stage software engineering.
• You have experience optimising solution performance with a constrained set of technologies.
• You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering.