Senior AWS Data Engineer

Quick Facts

• Role: Senior AWS Data Engineer

• Location: Charlotte, NC (Onsite)

• Duration: Long-term

Description

Senior AWS Data Engineer responsible for designing, developing, and optimizing scalable data pipelines and distributed data processing workflows on AWS. You will build and maintain production-grade Java/Python backend services and RESTful APIs, integrate microservices, and work with AWS data services. The role also includes integrating MCP/LLMs/generative AI capabilities into APIs and enterprise workflows.

Responsibilities

• Design and optimize scalable data pipelines and data processing workflows using Python, PySpark, and SQL

• Develop, enhance, and maintain production-grade APIs and backend services using Java and Python

• Build and integrate RESTful APIs and microservices for data-driven applications and enterprise integrations

• Leverage AWS services (S3, Glue, EMR, Lambda, Redshift) to deliver scalable data engineering solutions

• Integrate Model Context Protocol (MCP), Large Language Models (LLMs), and generative AI into applications and workflows

• Write reusable, maintainable, and scalable code using object-oriented principles and design patterns

• Write and optimize complex SQL and implement efficient ETL/ELT for large-scale transformations

• Collaborate across engineering and business teams to translate requirements into solutions

• Troubleshoot issues across APIs, data pipelines, integrations, and cloud applications

• Participate in code reviews, automated testing, CI/CD, performance tuning, and production support

Requirements

• Hands-on development experience in data engineering, backend development, or software engineering

• Strong hands-on AWS data/cloud experience including S3, Glue, EMR, Lambda, and Redshift

• Proven production experience building RESTful APIs and backend services with Java (design, integration patterns, error handling)

• Strong Python skills for reusable modules, backend components, and API integrations

• Hands-on PySpark and distributed data processing experience for scalable transformations and optimized pipelines

• Proficiency in SQL (complex queries, transformations, and performance optimization)

• Strong OOP and maintainable architecture fundamentals

• Exposure to MCP, LLMs, generative AI, or AI integration with an understanding of API/enterprise workflow integration

• Experience with API testing, debugging, authentication, and authorization

• Familiarity with Git, CI/CD pipelines, automated testing, and Agile development practices