Why This Role Stands Out
This hybrid AI Data Engineer role offers exciting opportunities to leverage your advanced Python and OpenAI expertise on impactful, cloud-native solutions, with a competitive hourly rate of $87. You'll thrive here if you're a skilled data engineer passionate about building scalable AI-driven pipelines and collaborating within a dynamic technology environment. Apply today to contribute to cutting-edge projects with significant potential for professional growth.
Quick Overview
Job Description
Job Title: AI Data Engineer
Location: Remote
Duration: 12 Months + Extension
Bill Rate: $91/hr on C2C
Job Type: C2C/1099 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Descriptions:
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.
Key Responsibilities:
- Design, develop, and optimize advanced Python applications for data and AI use cases.
- Build and integrate OpenAI-based solutions (LLMs, prompt engineering, APIs, embeddings).
- Develop and maintain ETL/data pipelines 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 with data scientists, analysts, and business teams to deliver high-quality data solutions.
- Ensure best practices for performance, security, scalability, and reliability.
Required Skills & Qualifications:
- Strong and advanced Python development experience.
- Hands-on experience with OpenAI / Generative AI APIs.
- Solid experience with AWS cloud services.
- Proven expertise in Airflow for orchestration.
- Experience with Harness for CI/CD.
- Strong ETL and data engineering skills (data modeling, transformations, pipelines).
- Strong SQL and data analysis capabilities.
- Experience working in Agile/DevOps environments.
Preferred Qualifications:
- Prior experience in financial services or investment management domains.
- Exposure to large-scale, enterprise data platforms.
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