> Markdown version of [/jobs/ext/1356001-sr-software-engineer-i-global-servicing](https://www.wearedevelopers.com/jobs/ext/1356001-sr-software-engineer-i-global-servicing). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer I - Global Servicing... - **Company:** American Express Company - **Location:** Charlotte, NC, United States - **Experience:** Expert - **Salary:** $123,000.0 - $215,250.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Business Analytics Applications, Data Analysis, Build Automation, Microsoft Azure, BigQuery, Cloud Storage, Code Review, Continuous Delivery, Data as a Services, Data Governance, Extract Transform Load (ETL), Data Virtualization, DevOps, Distributed Computing Environment, Python (Programming Language), Enterprise Messaging Systems, Meta-Data Management, NoSQL, Cloud Services, Cloudera, Search Technologies, Software Engineering, SQL Databases, Data Streaming, Systems Integration, Speech Recognition, Working Model 2D, Enterprise Data Management, Data Processing, Google Cloud, Enterprise Software Applications, Data Ingestion, Large Language Models, Apache Spark, Spring-boot, Generative AI, Backend, Git, Data Layers, Pyspark, Kubernetes, Data Lineage, Deployment Automation, Google Cloud Functions, Data Analytics, Google Bigquery, Apache Kafka, Data Management, Speech Synthesis, Software Coding, Restful APIs, Terraform, Webhooks, Data Pipelines, Docker, Jenkins - **Published:** July 20, 2026 - **Apply:** https://www.juju.com/job/00000000gi2bz2 ## About the Role + 8+ years of professional experience designing and building cloud-native data platforms, scalable data pipelines, and distributed data processing solutions. + Strong experience designing and implementing batch and streaming data ingestion frameworks, ETL/ELT pipelines, and reusable data processing patterns using Python, PySpark, Spark, Dataproc, SQL, or equivalent distributed data processing technologies. + Experience designing and developing data platforms on Google Cloud Platform (preferred) or AWS/Azure using services such as BigQuery, Cloud Storage, Pub/Sub, Dataproc, Cloud Composer, Cloud Run, Cloud Functions, and related cloud-native data services. + Strong understanding of Contact Center as a Service (CCaaS) platforms and customer interaction data generated across voice, chat, IVR, dialers, Agent Assist, Speech-to-Text (STT), Text-to-Speech (TTS), conversation transcripts, interaction events, and operational metrics. + Experience defining canonical data models, metadata management, data quality frameworks, and reusable data products to support enterprise analytics, reporting, and downstream applications. + Experience integrating CCaaS platforms and enterprise systems using REST APIs, event streaming, messaging technologies, webhooks, and batch or real-time ingestion patterns. + Strong experience with Apache Kafka, Google Pub/Sub, or similar event streaming technologies, including designing scalable and resilient data ingestion patterns. + Strong proficiency in SQL, data modeling, data virtualization, semantic datasets, and working with relational and NoSQL databases supporting analytical and operational workloads. + Experience enabling enterprise analytics through BigQuery, Metrics as a Service, reusable data services, and cloud-native analytical platforms. + Experience implementing CI/CD practices, deployment automation, and engineering best practices using Git, Jenkins, Docker, Kubernetes, Terraform, or similar DevOps technologies. + Experience leading technical design discussions, mentoring engineers, conducting design and code reviews, and driving engineering best practices across multiple teams. + Excellent communication and stakeholder management skills with the ability to collaborate across Product, Engineering, Architecture, Analytics, and Business organizations to deliver scalable data platform solutions. Good to Have: + Experience with Java and Spring Boot for backend services supporting enterprise data platforms or APIs. + Experience with Context Management, Customer Journey Analytics, Customer Interaction Platforms, Contact Center Analytics, or Customer 360 solutions. + Familiarity with Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, vectordatabases, AI agents, or AI-powered analytics. + Experience with data virtualization, enterprise semantic layers, or reusable data services supporting analytics and reporting. + Experience modernizing enterprise data platforms or migrating analytical workloads to Google BigQuery and cloud-native data ecosystems. + Exposure to enterprise data governance, metadata management, data lineage, cataloging, or observability platforms. ## Description + Provide thought leadership, engineering expertise, and direction to the engineering teams; be versatile and be able to collaborate with business stakeholders, product teams and cross functional technology groups to drive continuous delivery. + Drive user story analysis and elaboration, design and develop software applications, and test and build automation tools. + Own all technical aspects of software development (architecture, design, and development of systems) for assigned applications. + Perform hands-on software development, writing code, API specs, doing proof of concepts, conducting code reviews, and testing in ongoing sprints. + Drive consistent development practices - tools and common components. + Develop deep understanding of tie-ins with other systems and platforms within the supported domains. + Work with technical product managers contributing to blueprints and assisting with annual planning of feature sets. + Identify opportunities for adopting new technology to solve existing needs and predicting future challenges. + Effectively communicate to internal and external business partners on solution design., We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Got AI ideas but no money? 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