Data Engineer

Talentola; Charlotte (NC); On-site; USD 103,000 - 110,000; Full time

Job summary

Talentola in Charlotte, NC is seeking a Senior Data Engineer - AWS to design, build, and optimize scalable data pipelines and APIs. You will work onsite, leveraging AWS services (S3, Glue, EMR, Lambda, Redshift) and Python/Java to deliver robust data-driven solutions.

You will collaborate with data scientists and engineers, implement CI/CD, and ensure high performance and reliability of data applications in a production environment.

Qualifications

• Hands-on development with data engineering, backend or software engineering.
• Strong AWS data services experience (S3, Glue, EMR, Lambda, Redshift).
• Production-grade API/backend development using Java with RESTful design.
• Strong Python skills for modular backend components.
• PySpark and distributed data processing experience.
• Strong SQL skills and query optimization.
• Solid OO design, patterns, and maintainable architecture.
• Familiar with MCP/LLMs or AI integration into APIs.
• Experience with API testing, authentication, and CI/CD.

Responsibilities

• Design, develop, and optimize scalable data pipelines using Python, PySpark, and SQL.
• Build and maintain production-grade APIs and backend services in Java and Python.
• Create RESTful APIs and microservices to support data-driven apps.
• Leverage AWS S3, Glue, EMR, Lambda, and Redshift to run data solutions.
• Work with MCP, LLMs, and AI to integrate AI-powered workflows.
• Write reusable, maintainable code using OO principles and design patterns.
• Write and optimize complex SQL and ETL/ELT processes.
• Collaborate with engineers, data scientists, and stakeholders.
• Troubleshoot issues across APIs, pipelines, and cloud apps.
• Participate in code reviews, testing, CI/CD, and production support.

Skills

AWS data services

PySpark

Python

Java

SQL

REST APIs

API integration

CI/CD

Distributed data processing

Tools

S3

Glue

EMR

Lambda

Redshift

Git

Job description

Senior Data Engineer - AWS

Charlotte, NC (Onsite)

6 Months+

Payrate: $75/hr to 80/hr C2C submission rate

IP: Global Logic

Required Skills & Qualifications

• Data engineering, backend development, or software engineering, with demonstrated hands-on development experience.
• Strong hands-on experience with AWS data and cloud services, including services such as S3, Glue, EMR, Lambda, and Redshift.
• Proven experience developing and maintaining production-grade APIs and backend services using Java, with a strong understanding of RESTful API design, integration patterns, and error handling.
• Strong programming skills in Python, with hands-on experience building reusable modules, backend components, or API integrations.
• Hands-on experience with PySpark and distributed data processing, including developing scalable data transformations and optimising data pipelines.
• Proficiency in SQL, including complex queries, data transformations, and query performance optimisation.
• Strong understanding of object-oriented programming, software design principles, data structures, and maintainable application architecture.
• Practical exposure to MCP, LLMs, generative AI, or AI application integration, with an understanding of how AI capabilities can be integrated into APIs and enterprise workflows.
• Experience with API testing, debugging, authentication and authorisation, and application integration.
• Familiarity with Git, CI/CD pipelines, automated testing, and Agile development practices.
• Strong problem-solving, communication, and collaboration skills, with the ability to work independently on complex technical requirements.

Preferred Qualifications (Nice to Have)

• Experience building AI-enabled applications, LLM-powered workflows, or MCP-based integrations.
• Exposure to LLM orchestration frameworks, tool calling, retrieval-augmented generation (RAG), or enterprise AI integration patterns.
• Experience with AWS-native AI services and deployment of AI-enabled applications in cloud environments.
• Familiarity with API gateways, containerisation, microservices architecture, and application observability.
• Experience with data warehousing, distributed computing, Spark performance tuning, and data quality frameworks.

Job Responsibilities

Key Responsibilities

• Design, develop, and optimise 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, with a strong focus on API design, integration, performance, and reliability.
• Build and integrate RESTful APIs and microservices to support data-driven applications and enterprise integrations.
• Leverage AWS services such as S3, Glue, EMR, Lambda, Redshift, and other relevant cloud-native services to build and manage scalable data engineering solutions.
• Work with Model Context Protocol (MCP), Large Language Models (LLMs), and generative AI technologies to develop or integrate AI-enabled applications and workflows.
• Implement reusable, maintainable, and scalable code using object-oriented programming principles, design patterns, and established engineering best practices.
• Write and optimise complex SQL queries and implement efficient ETL/ELT processes for large-scale data transformations.
• Collaborate with data engineers, application developers, architects, data scientists, and business stakeholders to translate requirements into robust technical solutions.
• Troubleshoot and resolve issues across APIs, data pipelines, integrations, and cloud-based applications.
• Participate in code reviews, automated testing, CI/CD implementation, performance tuning, and production support while adhering to engineering standards.