System Reliability Engineer (SRE) // Motionlogic
Are you a software engineer who wants to become a system engineer?
Do you want to write software that operates Big Data platforms that process Terabytes per day with cutting edge technologies?
Do you want to show how you can build a really highly available and secure system?
Then read on!
About the job
Motionlogic is trying to give answers to big questions and it is trying to use really big data to do so. We are building data products and the infrastructure that can handle 100s of Terabytes, billions of events daily and provide actionable insights in near real time.
Does it sounds fun and challenging? If yes, that what you'll have to do when you show up in the office:
- Design, write and deliver software to improve the availability, scalability, latency and efficiency of Motionlogic's platforms and services.
- Solve problems occurring in critical services and build automation to prevent the recurrence of them.
- Partner with the Data Engineering and Machine Learning teams in order to incorporate their produced artifacts to the deployed platforms.
- Employ monitoring tools to collect KPIs, interpret them to optimize the operational profile and prohibit problems from recurring.
- Build Big-Data appliances which will operate in secure data centers all around the planet.
- Build the automation that will build, deploy and monitor the infrastructure you designed.
- Select which new technologies to incorporate in the existing tool chain.
- Automate the operation of internal systems.
- Improve continuously, you will be encouraged and rewarded for it.
Expected skills and experience
If you are up for the challenge, we think you should carry some of the following skills and experiences:
- Self driven personality.
- BS degree in Computer Science, another quantitative field, or equivalent practical experience.
- Experience with algorithms, data structures and software design.
- Experience in at least one high level language like Ruby and Python.
- Experience in designing, analyzing and troubleshooting Big Data systems.
- Familiarity with running data pipelines on premise installations.
- Experience with scripting in Python and bash.
- Exposure onvirtualization engines (libvirt and qemu) and automating their operational aspects.
- Knowledge of container technologies, like LXC and Docker.
- Knowledge of at least one monitoring solution like Prometheus, Nagios, Munin or Zabbix.
- Knowledge on operating big data technologies (YARN, Mesos, Zookeeper, etc.).
- Analytical skills and passion for measuring everything and improving systems based on the insights gained from the measured data.
If it sounds something you like to know more about don't hesitate to contact us!
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