Lead Senior Data Engineer Agentic AI
Location: Tallahassee, FL, USA
Duration: 12 Months + Extension
Bill Rate: $85/hr on C2C
Job Type: C2C/1099 Contract
Client: To Be Discussed Later
Work Authorization: US-Citizen, H-1B, OPT-EAD, GC-EAD
Job Description:
We are seeking an experienced Data Engineer to design, develop, and optimize modern data platforms while building AI-powered data solutions. The ideal candidate will have strong expertise in cloud data engineering, Snowflake, and AI-driven architectures, with hands-on experience in Agentic AI, Multi-Agent Orchestration, and Snowflake Cortex. This role requires developing scalable data pipelines, integrating AI agents into enterprise workflows, and enabling intelligent data applications.
Required Experience
5+ years of experience in Data Engineering or Data Platform Development.
Strong experience working with cloud-based data platforms and modern data architectures.
Mandatory Skills:
Agentic AI application development.
Multi-Agent Orchestration frameworks.
Snowflake Cortex (Cortex AI, Cortex Analyst, Cortex Search, Cortex Functions).
Snowflake Data Cloud.
SQL and advanced query optimization.
Python programming.
ETL/ELT pipeline development.
Data modeling and data warehousing.
REST APIs and system integrations.
Git and CI/CD practices.
Preferred Skills:
Experience with LangGraph, CrewAI, AutoGen, or similar multi-agent frameworks.
Experience with LLMs and Retrieval-Augmented Generation (RAG).
Knowledge of vector databases and semantic search.
Experience with Azure, AWS, or Google Cloud Platform.
Apache Airflow, dbt, or similar orchestration tools.
Docker and Kubernetes.
Streaming technologies such as Kafka.
Key Responsibilities:
Design, build, and maintain scalable data pipelines and data platforms.
Develop AI-powered data solutions using Agentic AI and Multi-Agent architectures.
Build and optimize intelligent workflows using Snowflake Cortex capabilities.
Integrate LLMs with enterprise data while ensuring governance and security.
Design semantic search, RAG, and AI-assisted analytics solutions.
Develop and optimize Snowflake data models, stored procedures, and performance tuning.
Collaborate with Data Scientists, AI Engineers, Product Managers, and business stakeholders to deliver AI-enabled data products.
Ensure data quality, reliability, observability, and security across data platforms.
Automate deployment using CI/CD pipelines and Infrastructure as Code where applicable.
Stay current with emerging AI, GenAI, and Snowflake technologies and recommend best practices.
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