Aptino
Aptino

ETL Developer

Hybrid in Charlotte, NC, US • Posted 8 hours ago • Updated 8 hours ago
Contract Corp To Corp
Contract Independent
Contract W2
12 Months
No Travel Required
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Orchestration
  • FOCUS
  • Good Clinical Practice
  • Google Cloud
  • Google Cloud Platform
  • Data Quality
  • Data Validation
  • Extract, Transform, Load
  • Data Engineering
  • Data Integration
  • Data Modeling
  • Collaboration
  • Communication
  • Customer Service
  • Apache NiFi
  • Machine Learning (ML)
  • Performance Tuning
  • Artificial Intelligence
  • Cloud Computing
  • ELT
  • Alteryx
  • Amazon Web Services
  • Analytics
  • Apache Airflow
  • Technical Writing
  • Unstructured Data
  • Workflow
  • Management
  • Production Support
  • Scalability
  • Use Cases
  • ETL/ELT
  • Data Pipelines
  • GCP
  • AWS
  • Cloud Data Services
  • Pipeline Orchestration
  • Data Ingestion
  • Data Transformation
  • Performance Optimization
  • Error Handling
  • Structured & Unstructured Data
  • AI Ops
  • Agentic AI
  • Conversational AI
  • AI/ML
  • Data Architecture
  • Cloud-Native Solutions
  • Pipeline Monitoring
  • Cross-Functional Collaboration
  • Technical Documentation
  • ETL
  • Data Pipeline Development
  • Multi-Cloud
  • Cloud-Native ETL
  • Data Quality Frameworks
  • Troubleshooting
  • Reliability
  • Structured Data
  • Customer Operations
  • AI-Driven Transformation
  • AI Engineering
  • Analytics Platforms
  • Reusable Data Frameworks
  • Data Engineering Standards

Summary

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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90999382
  • Position Id: 9098293
  • Posted 8 hours ago
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AK

Anchal Khapekar

Recruiter @ Aptino
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