Are you challenged by driving Engineering Improvements and are you able to translate this into an operational environment for data engineering and data science?
Co-Develop, implement, deploy and maintain the environment in close co-operation with the internal customer and the solution team. This job is focused on enabling/deploying/optimizing GPU solutions in the analytics lab
As Data Ops engineer you will develop, extend, implement, deploy and maintain the data engineering and data science environment for the company. Your focus will be on working with the internal customer to optimize their data engineering and data science work. You will work closely together with the data analytics lab system engineers and application benchmark specialist to identify usability bottlenecks and will also drive the architectural evolution of the system to maximize framework and pipeline manageability and performance. You will be part of the devops team for the data analytics lab and HPDA (high performance data analytics) ecosystem and in that role also work closely together with all member of the team on all relevant stories in our sprints. Your main focus area will be on GPU computing, both for deploying/maintaining frameworks as well as optimizing/tuning GPU codes that run on the HPDA cluster.
Besides this your responsibilities include:
- Define improvement proposals that focus on usability and stability for the data engineering and data science ecosystem, with a focus on GPU’s;
- Strong partner in discussions with solution team system architect and other stakeholders within the internal customer departments;
- Drive progress towards internal and external partners for implementation of improvements;
- Keep abreast with relevant literature, means and methods;
At least master level or equivalent in computer science and/or Engineering.
Particularly relevant areas of expertise might include
- At least 5 years of relevant experience as data ops specialist;
- At least 5 years of relevant experience in GPU optimizations for NVIDIA gpu’s;
- C++ and python programming;
- Experience in developing large scale applications that scale across tens of GPU node’s
- Experience administering bare-metal, virtualized and containerized environments;
- Provisioning (preferred ansible);
- Experience with deploying and maintaining data engineering frameworks;
- Good understanding op CI/CD pipelines
- Experience with matlab is a pre;
- Experience with HPC or HPDA setups is a pre;
- Highly motivated team player.
- Shows initiative and problem solving attitude.
- Vision and opinion.
- Independent, accurate, systematic approach, problem solving.
- Pragmatic, practical, flexible and committed to quality.
- Excellent communication skills and proficiency in the English language.