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Senior Data Engineer II
American Express. Design and build highly scalable, resilient, and low-latency data platforms supporting mission-critical payment workloads .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and implementing large-scale distributed data platforms and systems, with a strong focus on AI-ready architectures and real-time data processing. Proficient in cloud-native technologies, microservices, and responsible AI principles to drive operational excellence and scalability.
Highest-signal resume keywords
Large-Scale Distributed Data PlatformsNoSQL TechnologiesData Pipeline DesignCloud-Native ApplicationsAI/ML Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PythonJavaScalaApache SparkCassandraElasticsearchCouchbaseRedisApache KafkaMicroservices
Soft Skills
Technical LeadershipCollaborationCommunicationMentoring
Tools & Technologies
DockerKubernetesOpenShiftCI/CDDevOpsMLOpsObservability
Industry Keywords
Responsible AIData GovernanceData PrivacyScalabilityResiliency
Tech Stack
Tools & technologiesApacheCassandraCloudDockerElasticSearchJavaKafkaKubernetesMicroservicesNoSQLOpenShiftPythonRedisScalaSpark
About the role
Key responsibilities & impact- Design and build highly scalable, resilient, and low-latency data platforms supporting mission-critical payment workloads
- Develop distributed data processing and real-time streaming pipelines capable of handling high-volume transactional data
- Build AI-ready data architectures and pipelines enabling machine learning, Generative AI, and real-time intelligence use cases
- Explore and implement Large Language Models, Retrieval-Augmented Generation, embeddings, vector search, and AI agents where appropriate
- Design and develop microservices, APIs, and event-driven architectures using modern engineering practices
- Drive adoption of cloud-native technologies, containerization, orchestration, CI/CD, automation, and observability
- Establish engineering practices for performance, scalability, resiliency, security, data quality, and operational excellence
- Apply Responsible AI and data governance principles, including privacy, security, explainability, model evaluation, and appropriate controls
- Evaluate emerging technologies across AI, data, and distributed computing and translate them into practical payment-platform solutions
- Provide technical leadership, mentor engineers, conduct design reviews, and contribute to engineering standards and best practices
- Partner with product, architecture, data science, and engineering teams to turn complex business opportunities into scalable technology solutions
Requirements
What you’ll need- Experience designing, implementing, and operating large-scale distributed data platforms and systems
- Strong experience with NoSQL technologies such as Cassandra, Elasticsearch, Couchbase, or Redis
- Experience with large-scale distributed data processing technologies such as Apache Spark
- Strong programming experience with Python, Java, Scala, or similar languages
- Experience designing data pipelines, data models, APIs, and event-driven architectures
- Strong understanding of distributed system concepts, including scalability, reliability, resiliency, security, and performance
- Demonstrated ability to solve complex engineering problems and deliver production-grade solutions
- Preferred: Experience building AI/ML-ready data platforms supporting machine learning, Generative AI, or intelligent application use cases
- Preferred: Familiarity with Generative AI, LLMs, RAG, embeddings, vector databases/search, and AI agent architectures
- Preferred: Experience integrating AI/ML models and services into production environments
- Preferred: Familiarity with MLOps/LLMOps, including deployment, evaluation, monitoring, observability, governance, and lifecycle management
- Preferred: Experience with Apache Kafka and real-time distributed processing
- Preferred: Experience developing microservices and cloud-native applications
- Preferred: Experience with Docker, Kubernetes, OpenShift, CI/CD, DevOps, infrastructure automation, and production observability
- Preferred: Understanding of Responsible AI, data privacy, security, governance, and model risk considerations
- Preferred: Experience architecting large-scale systems with emphasis on availability, scalability, performance, resiliency, and cost efficiency
- Preferred: Strong communication, collaboration, and technical leadership skills, with ability to mentor engineers and influence technical direction
- Depending on factors such as business unit requirements, the nature of the position, cost and applicable laws, American Express may provide visa sponsorship for certain positions.
Benefits
Comp & perks- Competitive base salaries
- Bonus incentives
- 6% Company Match on retirement savings plan
- Free financial coaching and financial well-being support
- Comprehensive medical, dental, vision, life insurance, and disability benefits
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
- Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
- Free and confidential counseling support through our Healthy Minds program
- Career development and training opportunities