Capacity Planner II (Data Collection)

We are looking for a Capacity Planner to help ensure DigitalOcean has sufficient capacity in all its Data Centers for our customers. Reporting to the Capacity Planning Manager, this individual will be forecasting demand trends, analyzing and modeling data to enhance operational efficiency as new products and hardware architecture initiatives are rolled out.

• Support the data requirements of the Capacity Planning team by enhancing and maintaining the Capacity Planning database 
• Identify capacity-related concerns and proactively work with systems, network, and engineering teams to develop measurements and discover resolutions
• Create a Plan of Record using in-house developed modelling tools to find the right balance between data center resources and investments to meet revenue producing demand forecasts
• Help build capacity planning tools and work with cross-functional teams to deliver timely and accurate forecasts
• Ensure capacity constraints and assumptions are identified, tracked, and communicated
• Develop data pipeline requirements with data analytics teams to support historical data tracking, dashboard & reporting, key metrics, and daily demand analysis across all product lines
• Analyze how hardware architecture and product changes impact capacity and provide feedback to teams and upper level management
• Participate in ongoing capacity planning data analyses and perform custom analysis as special situations arise

• You like data and wrangling data. You are comfortable with data analytics and workflows, particularly dbt and Airflow.
• You are well versed with data structures, have strong SQL skills, and are comfortable designing and modifying tables in a live database supporting other users. 
• You have a background in performance management, systems administration or capacity planning
• You have experience communicating and collaborating across the entire organization including engineering, sales, finance and program management. 
• Skilled at data visualization
• You have experience with programming in Python, Perl, R or Julia with a data science emphasis. GoLang experience is a plus.
• Linear Programming optimization or discrete event simulation experience is desirable.
• BS or MS in Engineering, Computer Science or Mathematics will be given preference.
• You have strong analytical and communication skills, and a risk mitigation mindset and exhibit appropriate levels of urgency.
• Experience using virtualization will be given strong consideration.

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• . The salary range for this position is between $80,000.00 - $115,000.00 based on relevant years of experience and skills. Employees may qualify for a bonus in addition to base salary; bonus amounts are determined based on company and individual performance. We also provide equity compensation to eligible employees including grants of equity upon hire and the option to participate in our Employee Stock Purchase Program.
• You will work with some of the smartest and most interesting people in the industry. We are a high-performance organization that is always challenging our teams and employees to continuously grow. We maintain a growth mindset in everything we do and invest deeply in employee development through formalized mentorship and other internal programs. We provide all employees with reimbursement for relevant conferences, training, and education.
• In addition to cash and equity compensation, we also offer employees a competitive array of benefits. In the United States, these include health insurance, flexible vacation, retirement benefits, a generous parental leave program, and additional resources to support employees' overall well-being. While the philosophy around our benefits is the same worldwide, specific benefits may vary in other countries due to local regulations and preferences.
• We are an equal opportunity employer and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Department: Infrastructure #LI-Remote