{"id":1126467,"url":"https://alion.io/job/american-express-sr-data-engineer-ii","title":"Sr Data Engineer II","company":{"id":2209,"name":"American Express","domain":"americanexpress.com","url":"https://alion.io/company/american-express","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":98,"open_postings":81,"ghost_share":0.037,"stale_share":0.074,"repost_share":0.222,"time_to_fill_p50_days":9,"computed_at":"2026-11-07T05:47:08Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Phoenix, United States","Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":107000,"max_usd":204000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1181},"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Cassandra","optional":false},{"name":"CI/CD","optional":false},{"name":"Couchbase","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Embeddings","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Docker","optional":true},{"name":"Kubernetes","optional":true},{"name":"LLMOps","optional":true},{"name":"OpenShift","optional":true}],"status":"live","first_seen_at":"2026-09-22T20:27:22Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-07T18:14:21Z","board_verified":true,"closed_at":null,"days_open":46,"trust":{"level":"ok","repost_count":2,"flags":["repost"],"days_open":45},"description":"Joining Amex Tech means discovering and shaping your contribution to something big. Here, you can work alongside talented tech teams and build a unique career with the Powerful Backing of American Express. With a range of opportunities to work with the latest technologies, and a commitment to back the broader engineering community through open source, our mission is to power your success. Because Amex Tech is powered by our technology, our culture, and our colleagues.\nSenior Data Engineer - AI & Intelligent Payment Platforms\nAre you ready to help build the next generation of intelligent payment platforms?\nAmerican Express is making strategic investments in next-generation payment network products, data platforms, and AI-powered capabilities to support its global growth agenda.\nThe American Express Card Network operates as a highly distributed, near-real-time, low-latency platform designed for exceptional availability and resiliency-processing transactions around the world, 24 hours a day, 365 days a year.\nAs a Senior Data Engineer - AI & Intelligent Payment Platforms, you will help design, build, and evolve highly scalable, AI-ready data platforms that power critical payment capabilities and enable real-time intelligence, advanced analytics, machine learning, and Generative AI use cases.\nYou will work at the intersection of data engineering, distributed systems, cloud-native technologies, and AI, helping transform large-scale payment data into intelligent, secure, and reliable products and experiences.\n Design and build highly scalable, resilient, and low-latency data platforms supporting mission-critical payment workloads.\nDevelop distributed data processing and real-time streaming pipelines capable of handling high-volume transactional data.\nBuild AI-ready data architectures and pipelines that enable machine learning, Generative AI, and real-time intelligence use cases.\nExplore and implement emerging AI capabilities, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embeddings, vector search, and AI agents, where appropriate.\nDesign and develop microservices, APIs, and event-driven architectures using modern engineering practices.\nDrive adoption of cloud-native technologies, containerization, orchestration, CI/CD, automation, and observability.\nEstablish engineering practices for performance, scalability, resiliency, security, data quality, and operational excellence.\nApply Responsible AI and data governance principles, including privacy, security, explainability, model evaluation, and appropriate controls.\nEvaluate emerging technologies across AI, data, and distributed computing and translate them into practical solutions for payment platforms.\nProvide technical leadership, mentor engineers, conduct design reviews, and contribute to engineering standards and best practices.\nPartner with product, architecture, data science, and engineering teams to turn complex business opportunities into scalable technology solutions.\n Minimum Qualifications\nExperience designing, implementing, and operating large-scale distributed data platforms and systems.\nStrong experience with NoSQL technologies such as Cassandra, Elasticsearch, Couchbase, or Redis.\nExperience with large-scale distributed data processing technologies such as Apache Spark.\nStrong programming experience with Python, Java, Scala, or similar languages.\nExperience designing data pipelines, data models, APIs, and event-driven architectures.\nStrong understanding of distributed system concepts, including scalability, reliability, resiliency, security, and performance.\nDemonstrated ability to solve complex engineering problems and deliver production-grade solutions.\nPreferred Qualifications\nExperience building AI/ML-ready data platforms supporting machine learning, Generative AI, or intelligent application use cases.\nFamiliarity with Generative AI, LLMs, RAG, embeddings, vector databases/search, and AI agent architectures.\nExperience integrating AI/ML models and services into production environments.\nFamiliarity with MLOps/LLMOps, including deployment, evaluation, monitoring, observability, governance, and lifecycle management.\nExperience with distributed messaging and streaming platforms such as Apache Kafka.\nExperience with real-time distributed processing using technologies such as Spark, Kafka, Cassandra, and Elasticsearch.\nExperience developing microservices and cloud-native applications.\nExperience with Docker, Kubernetes, OpenShift, or similar container platforms.\nExperience with CI/CD, DevOps, infrastructure automation, and production observability.\nUnderstanding of Responsible AI, data privacy, security, governance, and model risk considerations.\nExperience architecting large-scale systems with an emphasis on availability, scalability, performance, resiliency, and cost efficiency.\nAbility to stay current with emerging AI and data engineering technologies and identify opportunities to apply them to real-world business problems.\nStrong communication, collaboration, and technical leadership skills, with the ability to mentor engineers and influence technical direction.\nDepending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain 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