We’re at a turning point in history. Climate change is changing the world faster than ever before. Utilities will play a crucial role in the transformation of our society to fight climate change and become carbon-neutral, while at the same time making sure people and businesses can continue to use energy supply like they’ve been used to for so many years.
At Gorilla, we’re determined to not stay aside, but to make a real impact on the utility industry by providing data services that allow utilities to play the role they need to play in the quest for a net-zero society. By building something that solves a real problem, and by being the best at what we do.
You’re a stickler for code quality and performance. You’ve been coding Python for a while now and you are enthusiastic about the Python ecosystem. Configuration, performance, and scalability are your commandments: you code, test, troubleshoot, debug and document intricate python algorithms. As a data professional, you’re committed to create the best, most efficient, formulas that will transform massive amounts of client data into actionable output. You play a key role in the development and deployment of Gorilla for our clients. We believe in giving people responsibility and control over their work: as one of our engineers, we expect you to rise to the challenge. You work as part of a multidisciplinary squad, where your expertise is a vital part of your project’s success. And as a company, we like to work smart. We’re always improving our processes – who knows, you might even get enthusiastic about code reviews. Every two weeks, our meetups are the platform for you to share and expand your knowledge and technology expertise. And you’ll always get to learn from your team members too!
- You are responsible for building high quality industry-specific python algorithms and data transformation jobs for our global clients.
- You work together with the solution architect, subject matter expert and project manager in a project setup to meet client requirements within the set out timelines.
- You write elegant code in Python, using pandas as your main data analysis library. Runtime or memory performance benchmarking and improvements are part of your day-to-day task.
- Together with the data engineering team, you always look for process improvements to deliver the most elegant, performant and robust formulas possible.