Data Engineer, Edge Services

Our team operates and scales the Edge platform and Content Delivery Network that powers TikTok in the United States. We sit on top of one of the world's largest CDN footprints, processing massive volumes of measurement telemetry and edge access logs every day to deliverlow-latency, highly available video and live experiences to hundreds of millions of users.As a Data Engineer on the US Tech and Product — Edge and CDN team, you will build, optimize, and scale the data backbone that turns this firehose of operational data into actionable intelligence. Leveraging TikTok's comprehensive data platform — data lakes, message queues, caches, streaming engines, and OLTP/OLAP warehouses — you will partner with site reliability engineers, capacity engineers, and business stakeholders to power smarter alerting, leaner infrastructure cost, sharper capacity planning, and richer business insights for the Edge and CDN organization.

Responsibilities

• Design and implement high-concurrency, real-time streaming pipelines (using Flink, Spark Streaming, or Kafka) that ingest and process CDN measurement data, edge access logs, and infrastructure telemetry at hyperscale.
• Lead the design and maintenance of high-quality offline and real-time data warehouses, ensuring robust ETL/ELT processes that consolidate edge, network, and client-side data into a unified source of truth.
• Build data and analytics products that drive intelligent SRE — feeding statistical and ML-assisted anomaly detection, alerting, and root-cause analysis for the global edge fleet.
• Develop cost attribution and optimization datasets that quantify edge resource spend (bandwidth, compute, storage, peering) and surface optimization opportunities across PoPs, ISPs, and product lines.
• Build demand forecasting and capacity planning datasets that combine historical traffic, seasonality, growth, and event signals to inform procurement and deployment of edge capacity.
• Design and deliver dashboards, compasses, and self-service analytics that surface the health, performance, cost, and growth of the Edge and CDN platform to engineers, leaders, and cross-functional partners.
• Establish proactive monitoring, data quality, and lineage frameworks to ensure pipeline stability and the integrity of critical business and reliability metrics.

Minimum Qualifications

• Bachelor's degree or higher in Computer Science, Data Engineering, or a related quantitative field.
• 3+ years of experience in data engineering, building production-grade real-time and offline pipelines on Big Data platforms.
• Strong proficiency in SQL and at least one of Python / Java / Scala / Go, with hands-on experience using distributed processing frameworks (Spark, Flink, or equivalent) and streaming systems (Kafka, Pulsar, or equivalent).

Preferred Qualifications

• Experience operating at hyperscale on data lake / lakehouse architectures (Hudi, Iceberg, Delta) and OLAP engines (ClickHouse, Doris, Presto/Trino).
• Domain experience with CDN, edge, networking, or large-scale infrastructure telemetry (access logs, RUM, NetFlow, peering data), and SRE/observability use cases such as anomaly detection and SLO analytics.
• Demonstrated leadership and self-direction; strong written and verbal communication skills, with a willingness to both teach others and learn new techniques.