Data Engineer - Marketing Analytics

Kforce's client in Phoenix, AZ is looking for a Data Engineer with strong expertise in AWS, Python, and Conversational Analytics, with a focus on secure, scalable, and resilient systems. This role will focus on developing knowledgebases and agentic AI solutions that allow business users to interact with data through natural language, while ensuring reliability, scalability, and efficiency across AWS cloud infrastructure. Key Responsibilities:

• Design, build, and optimize data pipelines using AWS
• Implement security best practices across data and AI pipelines
• Develop and maintain knowledgebases and agents; Integrate structured and unstructured data sources
• Design and deploy Agentic AI workflows that autonomously orchestrate multi-step data retrieval, reasoning, and response generation
• Implement and support machine learning workflows in SageMaker for model training, deployment, and monitoring
• Leverage AWS Bedrock to build and deploy conversational and agentic AI solutions
• Ensure data lineage and quality control across all conversational and agentic AI systems
• Automate orchestration, monitoring, and logging for data pipelines and conversational agents
• Build and maintain CI/CD pipelines to enable secure, automated, and reliable deployments
• Collaborate with analytics, product, and business teams to design solutions that improve decision-making and data democratization
• Master's degree in computer science, Artificial Intelligence, Software Engineering, or a closely related engineering or AI research field is required
• Bachelor's degree with exceptional hands-on experience in data engineering and agentic AI may be considered on a case-by-case basis
• 5+ years of hands-on experience with AWS services including S3, Athena, Lambda, Step Functions, Redshift Serverless, SageMaker, Bedrock, ECS, and API Gateway
• Strong proficiency in Python for data engineering, automation, and API integration
• Hands-on experience designing and implementing Agentic AI systems - including multi-agent orchestration, tool use, memory management, and autonomous task execution
• Experience with agent frameworks such as AWS Bedrock Agents, Lang Chain, or similar orchestration frameworks
• Strong SQL skills and familiarity with large-scale data environments
• Solid understanding of ETL design, orchestration, and optimization in cloud platforms

• Experience with LLM integration into business workflows
• Familiarity with Lakehouse frameworks such as Iceberg or Delta for scalable analytics
• Experience with DevOps and Infrastructure-as-Code tools such as Terraform or CloudFormation
• Familiarity with front-end technologies including HTML, CSS, and React for building user-facing components
• Experience with retrieval-augmented generation (RAG), embeddings, and vector databases
• Exposure to emerging Agentic AI patterns such as ReAct, Plan-and-Execute, and self-correcting agent loops
• Background in marketing analytics or customer intelligence use cases