• Lead the architectural design and technical roadmap for scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces) • Drive the development and optimization of ML-driven data routing, filtering, and transformation engines to reduce customer data volumes by 80%+ while preserving critical insights • Architect and implement real-time analytics and anomaly detection systems using advanced machine learning techniques and large language models • Design cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog, New Relic) • Establish robust monitoring, alerting, and observability solutions for distributed systems operating at enterprise scale • Lead cross-functional technical initiatives, collaborating with Product, Data Science, and DevOps teams to translate strategic vision into technical solutions • Drive system performance, cost efficiency, and reliability optimization through advanced profiling, testing, and infrastructure design • Provide technical leadership and mentorship to senior and junior engineers, establishing engineering best practices and culture • Evaluate and introduce emerging technologies in AI/ML, data engineering, and observability to maintain competitive advantage • Participate in technical decision-making forums and contribute to company-wide engineering standards and practices