Senior Capacity Engineer, Capacity Engineering

Role DescriptionAs a Senior Capacity Engineer, you will play a vital role in shaping and optimizing the infrastructure strategy for Dropbox's products and services. You'll use your expertise to lead impactful projects, drive cost efficiency, and create robust capacity plans to support our 800M+ user base across multiple product categories. Impact Areas: You'll be crucial in areas such as strategic capacity planning, cost optimization, and large-scale hybrid cloud infrastructure management. Your efforts will help maintain the stability and performance of our services while supporting long-term growth and cost efficiency.What You Will Gain: You will have a major impact on the future of Dropbox's infrastructure, helping drive scalability, reliability, and cost efficiency. You'll gain exposure to senior leadership and the opportunity to lead high-impact projects. This role offers a dynamic, collaborative environment where you can advance your expertise, contribute to innovative solutions, and build strong relationships across the organization.Our Engineering Career Framework is viewable by anyone outside the company and describes what's expected for our engineers at each of our career levels. Check out our blog post on this topic and more here.Responsibilities

• Own Product Capacity Planning and Cost Efficiency Strategy: Own the strategic roadmap for capacity planning and cost optimization across assigned Dropbox portfolio. Drive the conceptualization, development, and execution of initiatives in partnership with key stakeholders across platform, product, and infrastructure teams.
• End-to-End Demand Planning: Conduct in-depth analysis of usage patterns , growth forecasts, and business requirements at the product level. Translate these insights into platform and infrastructure needs and create comprehensive plans for build/buy strategies and execution.
• Champion Cost Visibility and Efficiency: Own cost transparency efforts and drive efficiency improvements across private and public cloud environments, improving gross margin.
• Develop TCO Models: Design and maintain Total Cost of Ownership (TCO) models for key platform components (e.g., storage, compute) and product surfaces (e.g., FSS, Dash) to support informed decision-making.
• Oversee Large-Scale Infrastructure Migrations: Lead projects related to the migration of data and services across private and public cloud environments, ensuring minimal disruption and optimization of cost and performance.
• Manage Cross-Functional Relationships: Serve as the primary point of contact with physical infrastructure teams (e.g. supply chain, data centers, network, hardware engineering) and software infrastructure teams (e.g. storage, compute, ML). Collaborate closely with finance and product teams to influence capacity planning and alignment.

• Bachelor's degree in Computer Science, Industrial Engineering, or a related technical field, or equivalent practical experience.
• Minimum of 7+ years of hands-on experience in capacity planning or a related field, focusing on designing, forecasting, supply demand matching and scaling infrastructure to support high-demand, large-scale environments.
• Proficiency in SQL and data modeling for analyzing large datasets and generating insights to support capacity planning and infrastructure optimization.
• Strong experience in designing and implementing scalable capacity and forecasting models, including storage, compute, and network infrastructure. Ability to architect end-to-end solutions for complex capacity challenges.
• Experience in cloud FinOps with strong capabilities in cost modeling, TCO analysis, and cost optimization for cloud and data center environments.

• Strong coding proficiency and experience with data engineering tools (e.g. Airflow, Databricks) to build scalable data pipelines and logging infrastructure to support capacity planning.
• Experience managing and optimizing large-scale environments running both private and public cloud infrastructure.
• Experience in network and/or power planning and forecasting with engineering and data science teams.
• Experience with operations research, mathematical optimization, and applying AI or machine learning to improve capacity planning.