# Subham Satapathy > Data & Agentic AI Engineer | Spark/Scala • AWS • Kubernetes | Backend Systems & Observability | Ex-Motorola • Ex-Samsung Location: San Francisco Bay Area, United States Profile: https://flows.cv/subhamsatapathy I’m a Software Engineer with 3+ years of hands-on experience building distributed backend systems, large-scale data pipelines, and cloud-native platforms across ad-tech, enterprise, and consumer-facing environments. My core strength lies in designing reliable, observable systems that operate at scale, turning complex data and infrastructure challenges into stable, production-ready solutions. I work extensively with Spark/Scala, Python, AWS, Kubernetes, and modern data infrastructure to build backend-heavy systems that process billion-scale datasets and support analytics, automation, and downstream product workflows. Across roles, I’ve delivered measurable performance improvements including 4× faster data pipelines, reduced system failures through observability-first design, and improved reliability of mission-critical production workloads. At the intersection of backend engineering, data infrastructure, and applied AI, I have: •⁠ ⁠Built and optimized Spark/Scala pipelines processing billion-scale identity graphs, reducing runtime from 4 hours to 1 hour through partitioning, memory-safe execution, and state optimization •⁠ ⁠Architected production-grade monitoring and observability using Datadog and Terraform, launching 10+ dashboards and alerts to track runtime, failures, executor OOMs, and data freshness •⁠ ⁠Designed scalable analytics pipelines persisting metrics to Apache Iceberg, enabling reliable downstream reporting and trend analysis •⁠ ⁠Automated content generation workflows using LLM-driven agents, cutting manual drafting time from hours to under 10 minutes and increasing publishing throughput •⁠ ⁠Improved backend performance and reliability through query optimization, indexing, and API tuning, reducing latency and improving throughput in high-traffic systems •⁠ ⁠Strengthened production stability through CI/CD pipelines, structured logging, testing, and infrastructure-as-code practices In addition to backend-focused roles, I’ve delivered end-to-end systems spanning APIs, data pipelines, cloud infrastructure, and developer tooling. My work emphasizes scalability, observability, and long-term maintainability rather than short-term fixes. I collaborate closely with product, data, and platform teams to ensure systems are robust, metrics are trustworthy, and engineering decisions align with real business outcomes. I value clarity in system design, ownership in execution, and measurable impact in production. ## Work Experience ### Software Engineer @ Rokt Jan 2025 – Present | San Francisco, CA •⁠ ⁠Optimized Spark/Scala identity-graph pipelines processing billion-scale datasets, reducing runtime from 4 hours to 1 hour (4× faster) through partitioning, persistence tuning, and memory-safe execution •⁠ ⁠Designed and implemented a “graph vitals” monitoring system computing 10+ statistical metrics (percentiles, distributions, time-window trends) to improve data reliability and downstream analytics •⁠ ⁠Built production-grade observability using Datadog + Terraform, launching 10+ dashboards and alerts to track runtime, failures, executor OOMs, shuffle spill, and data freshness •⁠ ⁠Persisted analytics outputs to Apache Iceberg, enabling consistent, queryable datasets for downstream reporting and decision-making •⁠ ⁠Collaborated with platform and data teams to improve pipeline stability and reduce on-call incidents across mission-critical workloads ### AI Software Engineer @ AI Growth Agent Jan 2025 – Jan 2025 | San Francisco Bay Area ### Software Engineer @ NiX Jan 2024 – Jan 2025 | United States ### Graduate Assistant Grader-ENPM612 System & Software Requirements @ University of Maryland Jan 2024 – Jan 2024 | College Park, Maryland, United States ### Graduate Assistant Grader- ENPM680 Secure Coding for Software Engineering @ University of Maryland Jan 2023 – Jan 2023 | College Park, Maryland, United States ### Software Engineer @ Motorola Solutions Jan 2022 – Jan 2023 | Bengaluru ### Research Intern @ Indian Institute of Science (IISc) Jan 2021 – Jan 2022 | Bengaluru, Karnataka, India Worked on Speech Recognition in Agriculture and Finance. -Funded by Bill and Melinda Gates Foundation. ### Mentor @ Coding Club Jan 2020 – Jan 2021 ### Software Engineering Intern @ Samsung India Jan 2021 – Jan 2021 | Bengaluru, Karnataka, India ### Data Science Intern @ Exposys Data Labs Jan 2020 – Jan 2020 | Bengaluru, Karnataka, India Worked on a customer segmentation project and deployed various machine learning algorithms to achieve the task. ## Education ### Master's Degree in Computer Software Engineering University of Maryland ### BE - Bachelor of Engineering in Electrical, Electronics and Communications Engineering RV College Of Engineering ## Contact & Social - LinkedIn: https://linkedin.com/in/subhamumd --- Source: https://flows.cv/subhamsatapathy JSON Resume: https://flows.cv/subhamsatapathy/resume.json Last updated: 2026-04-11