ETL Developer

Role: ETL Developer
Location: Charlotte, NC – Hybrid (3 days/week onsite)
Duration: 12 months

Position Overview:

We are seeking an experienced ETL Developer to design, build, and enhance scalable data pipelines supporting AI-driven Customer Operations and AI Ops initiatives. The role will focus on cloud-based data integration, pipeline orchestration, data quality, and reliable delivery across Google Cloud Platform and AWS environments.

Key Responsibilities:

• Design, develop, and maintain robust ETL/ELT pipelines using technologies such as Apache NiFi, Apache Airflow, and Alteryx for data ingestion, transformation, and delivery.

• Develop scalable data workflows across Google Cloud Platform (Google Cloud Platform) and AWS, utilizing appropriate cloud-native data services.

• Partner with Data Architects, AI/ML Engineers, Data Scientists, and Business Analysts to understand requirements and translate them into effective data pipeline solutions.

• Build data workflows supporting Agentic AI, Conversational AI, AI Ops, and customer-focused analytics use cases.

• Monitor and troubleshoot production pipelines, identifying performance, reliability, data-quality, and processing issues and implementing appropriate fixes.

• Apply best practices for workflow orchestration, error handling, data validation, pipeline monitoring, and performance optimization.

• Support large-scale processing of both structured and unstructured data across multi-cloud environments.

• Contribute to data engineering standards, reusable frameworks, technical documentation, and development best practices to improve solution quality and maintainability.

• Work closely with cross-functional teams to resolve complex data challenges and ensure timely delivery of scalable solutions.

Required Qualifications:

• 7+ years of experience in ETL/ELT development, Data Engineering, or a related technical discipline.

• Strong hands-on experience with Apache NiFi, Apache Airflow, and Alteryx.

• Proven experience designing and managing end-to-end data pipelines handling high-volume structured and unstructured data.

• Strong knowledge of Google Cloud Platform and AWS data services and cloud-based data integration architectures.

• Solid understanding of data modeling, data quality, data integration, pipeline orchestration, and production support.

• Experience troubleshooting and optimizing data pipelines for performance, scalability, reliability, and resilience.

• Ability to translate business and technical requirements into scalable and maintainable data solutions.

• Strong communication and collaboration skills, with experience working alongside AI engineers, data scientists, architects, developers, and business stakeholders.

• Experience supporting AI/ML, AI Ops, Agentic AI, or Conversational AI initiatives is highly desirable.