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# Data Engineer / Data Scientist

- **Company:** Damco Inc
- **Location:** United States
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Performance Management, Automation of Tests, Software Quality, Databases, Extract Transform Load (ETL), Python (Programming Language), Machine Learning, Software Construction, Data Ingestion, Large Language Models, Generative AI, Backend, AI Platforms, AWS Data Analytics, Data Pipelines, Microservices
- **Published:** September 4, 2026
- **Apply:** https://www.dice.com/job-detail/ff093e06-f9f0-4014-9cee-1be4a6e5202d

## About the Role

We are seeking an experienced Data Engineer / Data Scientist (AI/ML) to design, build, and deploy scalable data pipelines and AI/ML solutions on AWS. The ideal candidate will have strong expertise in Python development, ETL orchestration, AWS data services, Large Language Model (LLM) application engineering, and cloud-native architecture. The role requires hands-on experience in building production-grade AI solutions, implementing robust testing practices, and collaborating with cross-functional teams to deliver business-critical data and AI initiatives.

## Description

Design, develop, and maintain scalable ETL and data processing pipelines using AWS services such as Glue, Lambda, and Step Functions.
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Build and optimize data ingestion, transformation, and orchestration workflows across structured and unstructured data sources.
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Develop and deploy AI/ML and Generative AI solutions leveraging AWS AI services and foundation models.
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Design and implement LLM-powered applications using Amazon Bedrock, Bedrock Agents, and Strands Agents Framework.
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Build Retrieval-Augmented Generation (RAG) solutions, intelligent document processing workflows, and conversational AI applications.
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Develop APIs, microservices, and backend services using Python.
Work with Amazon DocumentDB, Aurora, and other cloud-native databases for scalable application development.
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Collaborate with Data Engineers, Data Scientists, Architects, Product Owners, and Business Stakeholders to deliver AI-driven solutions.
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Ensure adherence to software engineering best practices, code quality standards, security, compliance, and operational excellence.
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Implement automated testing, validation, monitoring, and deployment processes for data and AI applications.
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Troubleshoot and optimize data pipelines, AI models, and application performance.


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