Infrastructure Capacity Analytics Engineer at Vultr

This role is ideal for a data-savvy engineer who understands the nuances of physical hardware and cloud infrastructure. You should have at least 6 years of Python experience and a deep background in time-series forecasting. Vultr is looking for someone who can bridge the gap between "big data" and "big iron," turning telemetry from global data centers into actionable growth plans for compute and storage. The compensation range is $75,000–$90,000, which may be on the lower side for the "Mid-level" senior-heavy requirements, but the benefits package is exceptional. It includes 100% company-paid medical premiums, a 4% 401(k) match with immediate vesting, a $2,500 annual professional development budget, and unique long-term perks like a one-month paid sabbatical every five years. The role is fully remote within the US. **You might be a good fit if you...** * Have mastered Python libraries like Pandas and Scikit-learn to build predictive models (ARIMA, Prophet, XGBoost). * Can navigate complex SQL environments (specifically ClickHouse) to build robust ETL pipelines. * Enjoy translating technical infrastructure risks into high-level dashboards for executive stakeholders using Power BI or Grafana. * Have prior experience managing capacity for a cloud service provider or a massive distributed network.