Senior Site Reliability Engineer - Data-Centric Engineering
Akamai Technologies
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Do you like collaborating across teams to solve complex problems? Do you enjoy solving large scale distributed systems problems? Join the Mapping SRE team As Akamai Mapping Data-Driven SREs, we leverage advanced data science, statistical modeling, and machine learning to optimize the reliability, performance, and scalability of a global system routing trillions of daily client requests and tens of terabits of traffic per second. We analyze massive, high-dimensional datasets to discover predictive insights, design critical KPIs, and build advanced algorithmic monitoring infrastructure. Our unique data-first methodology allows us to precisely measure, model, and continuously optimize how our mapping architecture impacts customer performance. Partner with the best As a Data-Centric Site Reliability Engineer, you will apply rigorous quantitative analysis, statistical modeling, and machine learning to optimize the performance, availability, and routing algorithms of Akamai’s core Mapping Service. In this high-impact role, you will analyze massive telemetry streams, engineer predictive observability tools, and design data-driven architecture strategies. Operating at the forefront of data science and large-scale systems engineering, you will unlock deep analytical insights to diagnose and solve the internet’s most complex content delivery challenges. Note: This is a specialized data science and analytical engineering role requiring advanced quantitative and modeling expertise—not a standard DevOps, sysadmin, or routine operational position. As a Senior Site Reliability Engineer, you will be responsible for: Advanced Statistical Modeling: Develop mathematical, statistical, and machine learning models to analyze global traffic flows, predict latency anomalies, and optimize routing efficiency. Drive Observability & Analytics: Design, track, and refine data-driven SLIs/SLOs, utilizing exploratory data analysis to proactively identify hidden bottlenecks and systemic performance trends. Engineer Predictive Tooling: Build and deploy automated data pipelines, predictive models, and custom diagnostic algorithms to detect, prevent, and analyze complex platform anomalies. Advocate for Reliability: Partner with product engineers to champion scalable, resilient, and highly supportable system architectures. Influence Strategy: Provide data-driven insights to guide executive-level decision-making and identify high-impact technology investments. Deep Root-Cause Analytics: Conduct advanced quantitative investigations and forensic telemetry analyses on complex system outages and high-priority performance escalations. Do what you love To be successful in this role you will: Master’s or PhD in Data Science, Statistics, Computer Science, Machine Learning, or a highly quantitative analytical field. 5+ years of experience applying data science, predictive modeling, or quantitative research to large-scale distributed systems or tech environments. Deep mastery of Unix/Linux internals, computer networking protocols, and distributed system design. Professional fluency operating within a command-line UNIX/Linux computing environment. Data & Observability Expertise in statistical analysis, machine learning algorithms, time-series forecasting, and advanced SQL/NoSQL big data querying. Proven ability to transform complex datasets into actionable strategic roadmaps. Practical knowledge of enterprise observability, logging, and alerting systems like Grafana. Data Science & Communication Skills High proficiency in data science languages and frameworks (e.g., Python, R, Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch). Self-motivated communicator capable of articulating complex systems to non-technical stakeholders while managing multiple timelines. About us At Akamai, we make life better for billions of people, trillions of times a day. Whether you're streaming live events, scrolling social media, watching your favorite series, or managing your savings, we're…
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