We are seeking a Senior Principal Playback QoE Engineer to define and build the real-time quality intelligence layer for OVE. This role will connect viewer-side playback telemetry with OVE infrastructure behavior, enabling real-time live-event operations, customer-facing quality reporting, and data-driven optimization of the delivery platform.
Why OCI
- Build core technology for next-generation live streaming infrastructure
- Work on high-scale data systems tied directly to viewer experience
- Shape the QoE foundation for a greenfield media delivery platform
- Solve problems across playback, telemetry, networking, edge delivery, and analytics
- Influence how OVE proves quality, reliability, and customer value during major live events
Responsibilities
- Define OVE’s canonical playback QoE metric model
- Design and build real-time QoE telemetry pipelines using Kafka, Flink, or equivalent streaming systems
- Process large-scale playback events across sessions, devices, geographies, ISPs, app versions, protocols, and delivery paths
- Build real-time aggregations, anomaly detection, alerting, and live-event dashboards
- Correlate playback telemetry with OVE relay, control plane, routing, and fallback behavior
- Partner with player, infrastructure, observability, and product teams to improve end-to-end video quality
- Support customer-facing QoE reporting, post-event analysis, and operational reviews
- Identify playback regressions by device, region, ISP, app version, or delivery path
- Help define QoE-driven feedback loops for routing, failover, capacity planning, and event readiness
- Drive engineering standards for telemetry schemas, event quality, data correctness, and operational reliability
Internal Responsibilities
Qualifications
- 10+ years of experience in software engineering, data engineering, distributed systems, media platforms, or observability systems
- Strong understanding of video playback QoE metrics and streaming media behavior
- Hands-on experience with Kafka, Flink, Spark Streaming, Beam, Pulsar, or comparable large-scale streaming data systems
- Experience designing real-time pipelines using event-time processing, windowing, stateful aggregation, stream joins, and schema evolution
- Experience operating high-scale telemetry or observability systems with high-cardinality dimensions
- Strong systems debugging skills across client, edge, backend, and data processing layers
- Familiarity with HLS, DASH, low-latency streaming, CDN behavior, edge delivery, or player telemetry
- Experience supporting live-event streaming, large customer launches, or high-traffic operational events is a plus
- Experience with QoE analytics, anomaly detection, SLOs, customer dashboards, or incident response is a plus
- Strong programming skills in Java, Scala, Python, Go, or similar production engineering languages
Preferred Qualifications
- Experience with live sports, major broadcast events, or large-scale linear streaming
- Experience building command-center dashboards for real-time event operations
- Experience with Conviva, Mux Data, Datadog, Prometheus, Grafana, ClickHouse, Druid, Pinot, OpenSearch, or similar analytics and observability systems
- Experience correlating playback telemetry with CDN, edge, origin, or network data
- Experience defining customer-facing quality metrics, SLAs, SLOs, or post-event reporting
- Familiarity with MoQ, QUIC, WebRTC, low-latency HLS, or emerging streaming protocols
External Responsibilities
Qualifications
- 10+ years of experience in software engineering, data engineering, distributed systems, media platforms, or observability systems
- Strong understanding of video playback QoE metrics and streaming media behavior
- Hands-on experience with Kafka, Flink, Spark Streaming, Beam, Pulsar, or comparable large-scale streaming data systems
- Experience designing real-time pipelines using event-time processing, windowing, stateful aggregation, stream joins, and schema evolution
- Experience operating high-scale telemetry or observability systems with high-cardinality dimensions
- Strong systems debugging skills across client, edge, backend, and data processing layers
- Familiarity with HLS, DASH, low-latency streaming, CDN behavior, edge delivery, or player telemetry
- Experience supporting live-event streaming, large customer launches, or high-traffic operational events is a plus
- Experience with QoE analytics, anomaly detection, SLOs, customer dashboards, or incident response is a plus
- Strong programming skills in Java, Scala, Python, Go, or similar production engineering languages
Preferred Qualifications
- Experience with live sports, major broadcast events, or large-scale linear streaming
- Experience building command-center dashboards for real-time event operations
- Experience with Conviva, Mux Data, Datadog, Prometheus, Grafana, ClickHouse, Druid, Pinot, OpenSearch, or similar analytics and observability systems
- Experience correlating playback telemetry with CDN, edge, origin, or network data
- Experience defining customer-facing quality metrics, SLAs, SLOs, or post-event reporting
- Familiarity with MoQ, QUIC, WebRTC, low-latency HLS, or emerging streaming protocols
