About the Team: ByteDance Networking brings together innovative ideas and technologies from network architecture, software-defined networking (SDN), network virtualization, switch software and hardware co-design, and high-speed networking, to create hyperscale data-center networking solutions that power several of the most popular apps of the world such as Douyin and TikTok which serve hundreds of millions of users around the globe.
ByteDance Networking is responsible for designing, building, and operating the global, intelligent network infrastructure to meet the requirements of high availability, scalability, and high-performance.
About the Role: As a Senior Network Capacity & Planning Engineer, you will own end-to-end network planning for large-scale data center and backbone networks: translating product growth and traffic patterns into multi-quarter and multi-year capacity plans, identifying risk hotspots, driving investment and delivery priorities, and ensuring network scalability and resiliency.
You will be expected to operate with high autonomy, influence senior stakeholders, and partner across Network Engineering, SRE, DC/IDC delivery, Finance/Procurement, and product growth teams to turn planning into real build outcomes.
Responsibilities:
- Capacity Forecasting & Modeling
- Own and evolve models to forecast ByteDance global network traffic demand (DC, backbone, Cloud, peering/transit) across multiple horizons (weekly/quarterly/annual)
- Define forecast accuracy metrics, perform backtesting, and systematically improve methodology (seasonality, event-driven spikes, regional growth shifts, product launches)
- Network Planning
- Lead capacity planning and network expansion strategy: define headroom policies, redundancy targets, and growth triggers aligned with availability/SLA objectives
- Produce actionable network plans (quarterly and annual): where/when to add capacity, which links/PoPs/DC fabrics to scale, and which upgrades deliver best risk reduction and cost efficiency
- Run network simulations / what-if analysis to quantify failure-domain risk, congestion risk, and resiliency gaps; recommend topology or routing changes where appropriate
- Drive planning-to-execution alignment: translate plans into clear build requirements and timelines; track delivery progress and mitigate gaps (supply, lead time, deployment constraints)
- Own planning readouts for leadership: communicate assumptions, risks, trade-offs, and prioritization proposals with clarity
- Data & Tooling
- Build scalable methods and tools to streamline network data analytical tasks (pipelines, dashboards, automated insights)
- Partner with the OneNet team to automate forecasting and network planning workstreams (data ingestion, reporting, plan generation, validation, alerts)
- Cross-functional Leadership
- Engage with cross-functional teams to align on demand signals, validate model inputs, and integrate planning into business roadmaps
- Mentor/guide team members; provide best practices on planning frameworks, metrics, and data quality
- Reporting & Governance
- Deliver quarterly and annual summaries of key network planning and delivery performance metrics to internal stakeholders, including forecast accuracy, capacity utilization trends, risk posture, and delivery health
- Establish planning governance: standard definitions, review cadence, change management for assumptions and plan revisions
Requirements
Minimum Qualifications
- A Bachelor's or Master's degree in Computer Science, Information Science, Engineering, Mathematics, or equivalent
- Proven experience applying quantitative methodologies to analyze network performance and capacity metrics
- In-depth understanding of network devices, protocols, routing, and resiliency (e.g., BGP/IGP, ECMP, failure domains, traffic engineering concepts)
Preferred Qualifications
- Demonstrated ownership of network planning (capacity strategy, headroom policy, long-range planning, build prioritization) in hyperscale networks, large ISPs, or major cloud providers
- Experience collaborating with network engineers and building productive cross-functional relationships (Engineering, SRE, DC delivery, Finance/Procurement)
- Experience leading data science and engineering projects end-to-end (problem framing → model/tool delivery → adoption)
- Experience with data visualization software, e.g. Aeolus, Tableau
- Experience driving ambiguous problems to closure; comfortable influencing stakeholders without direct authority
- Coding experience in Python + SQL (MySQL or similar) and/or other languages for data analysis and automation