Capacity Analytics/Data Engineer
Long-term contract through 2027
Hybrid in Philadelphia, PA (2-4 days onsite)
This opportunity is for a Data Engineer/Capacity Analytics professional supporting private cloud infrastructure capacity planning and optimization. The role focuses on analyzing infrastructure demand, utilization, and capacity trends while developing forecasting models, reporting solutions, and automation capabilities. The environment supports technologies including VMware, OpenStack, Kubernetes, Docker, and storage platforms, with a strong emphasis on cost optimization, efficiency, and data-driven decision-making within a small, collaborative engineering team.
Responsibilities:
- Analyze infrastructure demand, utilization, and capacity data across private cloud environments.
- Build, maintain, and automate forecasting models to support capacity planning and resource optimization.
- Develop reporting, dashboards, and data visualizations to drive operational and strategic decisions.
- Monitor compute and storage utilization and proactively identify capacity risks and issues.
- Support the full lifecycle of capacity management, including planning, purchasing, deployment, and decommissioning activities.
- Identify opportunities to reduce waste, improve utilization, and optimize infrastructure costs.
- Work with large datasets to generate actionable insights and improve forecasting accuracy.
- Collaborate with engineering and architecture teams to support infrastructure planning initiatives.
- Drive automation and process efficiency improvements across capacity analytics and reporting functions
Qualifications:
- 3-5 years of experience in capacity planning, forecasting, modeling, analytics, or a related data-focused engineering role.
- Strong Excel skills, including pivot tables, raw data manipulation, and allocation versus provisioned capacity analysis.
- Experience creating dashboards, reports, and data visualizations.
- Strong SQL skills or proficiency with another query language.
- Experience working with large datasets and forecasting models.
- Ability to analyze complex data and provide actionable recommendations.
- Strong problem-solving skills with the ability to work effectively in ambiguous environments.
- Proven ability to identify risks early and focus on automation and operational efficiency.
Preferred Qualifications:
- Python scripting and automation experience.
- Familiarity with private cloud platforms and technologies such as VMware, OpenStack, Kubernetes, Docker, and storage environments.
- Experience with AI/ML concepts or projects.
- Demonstrated ability to modernize analytics processes and reduce dependence on manual Excel-based workflows.
