When at Base we’ve made the decision to progress into the next step of our product strategy, we’ve effectively entered on the path to building a new large-scale distributed system capable of crunching data and performing millions of computations – often of very different kinds and with different SLA’s. Imagine that instead of having to build a tool that does one thing well, you’re faced with the challenge of designing and implementing an analytics engine that combines the characteristics of best-of-breed data technologies and that, depending on the nature of the query, can select execution path best geared for it. This is what we’ve set out to do and have since been working on specifying a path that will take us there.
We are now ready to take this effort to the next level and to do this effectively we’re looking to grow our Data Products team. If you join us as Distributed Data Systems Engineer you’ll have a direct influence on the design and engineering decisions right from the very early days of this project. You’ll be crafting the future roadmap of this heterogeneous data system capable of working well under multiple usage patterns – whether interactive or batch – and effectively performing a broad range of calculations – be it statistical inference or different forms of machine learning. And finally, you’ll be working closely with and getting direct feedback from our Data Scientists and Machine Learning Engineers and in effect helping us fundamentally transform the way companies around the world sell.
If you see the magnitude of this challenge and it animates your builder’s imagination, then let us know and let’s discuss it further. For the right person, this could be the opportunity of a lifetime.
If you want to learn more about how we work, take a look here: https://lab.getbase.com/
- Participate in the design and implementation of a highly scalable system for serving interactive analytics queries and batch processing of large datasets.
- Lead the future direction of the analytics engine design.
- Build real-time distributed analytics query processor to serve analytics on big data.
- Optimize system performance and robustness to ensure a truly interactive user experience.
- Enable Data Scientists to work effectively.
- Design API’s that will enable robust visualisation capabilities.