Engineering Manager - Cloud Infrastructure

As an experienced Engineer joining our engineering team, you will be responsible for handling massive-scale data processing and analytics infrastructure supporting over 1B daily events, 3M+ DAU, and 50k+ hours of content. Your role will involve bridging the gap between raw data collection and actionable insights, while supporting our ML initiatives. **Key Responsibilities:** - Lead and scale the Infrastructure Pod, setting technical direction for data, platform, and DevOps initiatives. - Architect and evolve our cloud infrastructure to support 1B+ daily events, ensuring reliability, scalability, and cost efficiency. - Collaborate with Data Engineering and ML pods to build high-performance pipelines and real-time analytics systems. - Define and implement SLOs, observability standards, and best practices for uptime, latency, and data reliability. - Mentor and grow engineers, fostering a culture of technical excellence, ownership, and continuous learning. - Partner with leadership on long-term architecture and scaling strategy from infrastructure cost optimization to multi-region availability. - Lead initiatives on infrastructure automation, deployment pipelines, and platform abstractions to improve developer velocity. - Own security, compliance, and governance across infrastructure and data systems. **Qualifications Required:** - Previously a Tech Co-founder / Founding Engineer / First Infra Hire who scaled a product from early MVP to significant user and data scale. - 5 to 12 years of total experience, with at least 2+ years in leadership or team-building roles. - Deep experience with cloud infrastructure (AWS/GCP). - Experience with containers (Docker, Kubernetes), and IaC tools (Terraform, Pulumi, or CDK). - Hands-on expertise in data-intensive systems, streaming (Kafka, RabbitMQ, Spark Streaming), and distributed architecture design. - Proven experience building scalable CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and infrastructure for data and ML workloads. - Comfortable being hands-on when needed, reviewing design docs, debugging issues, or optimizing infrastructure. - Strong system design and problem-solving skills; understands trade-offs between speed, cost, and scalability. - Passionate about building teams, not just systems, can recruit, mentor, and inspire engineers. **Preferred Skills:** - Experience managing infra-heavy or data-focused teams. - Familiarity with real-time streaming architectures. - Exposure to ML infrastructure, data governance, or feature stores. - Prior experience in the OTT/streaming/consumer platform domain is a plus. - Contributions to open-source infra/data tools or strong engineering community presence. As an experienced Engineer joining our engineering team, you will be responsible for handling massive-scale data processing and analytics infrastructure supporting over 1B daily events, 3M+ DAU, and 50k+ hours of content. Your role will involve bridging the gap between raw data collection and actionable insights, while supporting our ML initiatives. **Key Responsibilities:** - Lead and scale the Infrastructure Pod, setting technical direction for data, platform, and DevOps initiatives. - Architect and evolve our cloud infrastructure to support 1B+ daily events, ensuring reliability, scalability, and cost efficiency. - Collaborate with Data Engineering and ML pods to build high-performance pipelines and real-time analytics systems. - Define and implement SLOs, observability standards, and best practices for uptime, latency, and data reliability. - Mentor and grow engineers, fostering a culture of technical excellence, ownership, and continuous learning. - Partner with leadership on long-term architecture and scaling strategy from infrastructure cost optimization to multi-region availability. - Lead initiatives on infrastructure automation, deployment pipelines, and platform abstractions to improve developer velocity. - Own security, compliance, and governance across infrastructure and data systems. **Qualifications Required:** - Previously a Tech Co-founder / Founding Engineer / First Infra Hire who scaled a product from early MVP to significant user and data scale. - 5 to 12 years of total experience, with at least 2+ years in leadership or team-building roles. - Deep experience with cloud infrastructure (AWS/GCP). - Experience with containers (Docker, Kubernetes), and IaC tools (Terraform, Pulumi, or CDK). - Hands-on expertise in data-intensive systems, streaming (Kafka, RabbitMQ, Spark Streaming), and distributed architecture design. - Proven experience building scalable CI/CD pipelines, observability stacks (Prometheus, Grafana, ELK), and infrastructure for data and ML workloads. - Comfortable being hands-on when needed, reviewing design docs, debugging issues, or optimizing infrastructure. - Strong system design and problem-solving skills; understands trade-offs between speed, cost, and scalability. - Passionate about building teams, not just