Overview:
Clarium is seeking a highly skilled and analytical Performance Engineer with strong expertise in predictive modeling, data analysis, and reporting. The ideal candidate will play a critical role in analyzing performance data and supporting the scalability and efficiency of our OpenShift container platform (OCP) and legacy application environments. If you're passionate about data-driven insights and performance engineering, we invite you to apply for this exciting opportunity.
Key Responsibilities:
- Maintain and enhance predictive models for performance engineering and capacity forecasting across OpenShift and legacy systems.
- Analyze production usage data to identify trends, anomalies, and capacity constraints.
- Collect and consolidate performance data from various sources (monitoring tools, logs, telemetry systems, etc.).
- Compare real-world usage with test environment simulations to refine forecasting models.
- Develop and maintain dashboards and visual reports on capacity headroom and performance metrics.
- Monitor infrastructure performance (CPU, memory, disk, etc.) and proactively identify optimization opportunities.
- Collaborate with engineering, DevOps, and business stakeholders to align capacity plans with future demand.
- Provide data-driven insights and recommendations to ensure optimal system performance and scalability.
- Document capacity planning strategies, models, and best practices.
Must-Have Skills:
- 7+ years of experience in data analysis, predictive modeling, or performance engineering.
- Strong hands-on experience with OpenShift container platform infrastructure.
- Solid background in data analysis and performance reporting.
- Excellent analytical thinking and problem-solving skills.
- Strong communication and collaboration skills.
- High attention to detail and accuracy.
Preferred Qualifications:
- Experience with containerization platforms (e.g., Docker, Kubernetes).
- Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
- Experience with monitoring/logging tools (e.g., Prometheus, Grafana, ELK).
- Proficiency in data visualization tools (e.g., Tableau, Power BI).
- Working knowledge of scripting languages (e.g., Python, Bash).
- Exposure to performance testing tools (e.g., JMeter, LoadRunner, Gatling).
- Understanding of DevOps methodologies and ITIL practices.
- Experience with agile project management tools and methodologies.
- Familiarity with business intelligence or data warehousing concepts.