Senior Data Engineer, CX

Overview

NiCE is seeking a Senior Data Engineer to join the CX Engineering team, with a focus on workforce management. The ideal candidate thrives in a fast-paced, collaborative environment, partnering with engineers, data scientists, and product teams to build real-time, production-grade solutions. This role emphasizes applying deep AWS experience to cutting-edge problems, including integrating large language models into customer-facing agentic workflows. Success is measured by enabling ML and feature teams to ship scalable, reliable, and easy-to-use machine learning and AI workflows that power the customer experience. You will have opportunities to drive innovation at both the application and infrastructure levels, and work across teams and backgrounds."

Responsibilities

• Partner with ML engineers, data scientists, and product engineering teams to translate business needs into technical solutions and ship production features across Playvox WFM and CoPilot for WFM.
• Build and maintain data pipelines to prepare and ready data for consumption in features.
• Design, build, and maintain scalable machine learning and generative AI workflows, including integrating Amazon Bedrock and proprietary/foundation models into agentic, customer-facing features.
• Automate steps across the ML/AI lifecycle - data preparation, model training, inference, deployment, and monitoring.
• Collaborate cross-functionally to ensure applications work seamlessly end to end, including developing the APIs or UX to help bring the feature to life.
• Leverage AI-assisted engineering practices - using tools like GitHub Copilot and Claude Code to accelerate development, testing, and code review.

Requirements

• 5+ years of hands-on experience as a Data Engineer or similar, building and deploying solutions on AWS.
• Hands-on experience with core AWS services: Lambda, S3, Glue, Athena, Kinesis, EC2/ECS, RDS, DynamoDB, and other database systems.
• Experience with NoSQL stores - desirable MongoDB or other document databases.
• Experience building and maintaining real-time, low-latency data streaming pipelines from multiple sources.
• Solid knowledge of SQL, data warehousing, ETL, and Data Lake / relational database concepts.
• Experience with source control (GitHub), CI/CD, and containerized deployment.
• Experience with distributed systems and microservice architecture.
• Experience with Apache Spark, AWS Step Functions, and Snowflake.
• Experience with agentic AI workflows or orchestration frameworks.
• Experience with Amazon Bedrock or other generative AI / LLM platforms.
• Experience with Kubernetes or similar container orchestration.
• Knowledge of IAM roles and security groups within AWS.
• Familiarity working with data science teams and productionizing machine learning models.
• Strong documentation and communication skills.

Role Type: Individual Contributor