Overview
On Site
USD 90-100
Full Time
Part Time
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
NLQ
SNOWFLAKE
PYTHON
Pytorch
cortex
Job Details
Job Title: Data Engineer (AI/NLQ)
Location: Miami, FL (osnite)
Type: 6 months CTH
Job Overview:
We are seeking a seasoned Data Engineer to support the implementation and optimization of Cortex and other AI-driven platforms. This role is pivotal in building scalable, governed data infrastructure that enables natural language querying and intelligent data retrieval across enterprise systems.
Key Responsibilities
- Cortex Implementation: Contribute to the deployment and integration of Cortex, enabling seamless NLQ (Natural Language Querying) experiences across the organization.
- Semantic Layer Design: Architect and maintain a governed semantic layer that ensures accurate, secure, and performant data access for AI tools and agents.
- Cross-functional Collaboration: Partner with AI Engineers and Functional Data Experts (FDEs) to model data for AI agents, retrieval pipelines, and analytics use cases-optimizing for correctness, scalability, and permissioning.
- Machine Learning Development: Design and implement machine learning algorithms and optimization models using frameworks such as PyTorch, TensorFlow, Scikit-Learn, and MLlib.
- Operationalization of AI Layers: Translate semantic models into production-ready AI layers that support real-time NLQ and retrieval workflows; experience with Cortex or similar platforms is highly desirable.
- Programming Expertise: Proficient in Python and familiar with modern software engineering practices.
- ELT & Data Quality: Skilled in ELT tooling (e.g., AWS Glue) and implementing robust data quality frameworks.
- Governance & Compliance: Deep understanding of enterprise data governance, PII handling, and audit requirements, including SOX-adjacent constraints.
Qualifications
- Minimum 5 years of hands-on experience in data engineering or analytics engineering, with proven success in production environments using Snowflake and cloud-based data warehouses.
- Demonstrated ability to build scalable, secure, and high-performance data systems that support AI/ML workflows
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