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
Duration: 6 Months + Extension
Bill Rate: $87/hour
Job Type: C2C/1099 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD & EAD
Job Description :-
Client is seeking a highly skilled 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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