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# AI Data Engineer

- **Company:** Propertyvalue Quantum Technologies Llc
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $185,120.0
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Big Data, Cloud Computing, Continuous Integration, Data as a Services, Extract Transform Load (ETL), Data Systems, DevOps, Python (Programming Language), Cloud Services, Systems Integration, Large Language Models, Data Pipelines
- **Published:** August 27, 2026
- **Apply:** https://www.dice.com/job-detail/74755e66-5076-4d92-874d-80846bcfaa1e

## About the Role

Client is seeking a highly skilled Senior Python / AI Data Engineer with strong expertise in advanced Python development, OpenAI integrations, and cloud-native data engineering on AWS. The ideal candidate will have deep experience building scalable data pipelines, AI-driven solutions, and production-grade ETL systems., * Strong and advanced Python development experience.

 * Hands-on experience with OpenAI / GenerativeAI APIs.
 * Solid experience with AWS cloud services.
 * Proven expertise in Airflow for orchestration.
 * Experience with Harness for CI/CD.
 * Strong ETL anddata engineering skills (data modeling, transformations, pipelines).
 * Strong SQL anddata analysis capabilities.
 * Experience working in Agile/DevOps environments.

Preferred Qualifications:

 * Prior experience in financial services or investment management domains.
 * Exposure to large-scale, enterprisedata platforms.

## Description

* Design, develop, and optimize advanced Python applications fordata and AI use cases.
 * Build and integrate OpenAI-based solutions (LLMs, promptengineering, APIs, embeddings).
 * Develop and maintain ETL/datapipelines for large-scale data processing.
 * Implement workflow orchestration using Apache Airflow.
 * Work with AWS services, including Helix (internal platforms if applicable),data services, and cloud infrastructure.
 * Manage CI/CD pipelines using Harness.
 * Collaborate withdata scientists, analysts, and business teams to deliver high-quality data solutions.
 * Ensure best practices for performance, security, scalability, and reliability.


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