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Junior Data & AI Engineer
PRI Technology
4 hours ago
Full-time
On-site
New York City, New York, United States
The Junior Data & AI Engineer will support data pipelines, cloud-based data solutions, and AI-enabled applications, including data preparation for connectors and reusable data products. The role requires strong programming and SQL fundamentals, hands-on exposure to Snowflake, and an interest in emerging AI technologies. The engineer will work under guidance from experienced colleagues; practical experience and willingness to learn are valued over expertise in every listed technology.
Key Responsibilities: · Develop and maintain data pipelines, SQL queries, and transformations using Snowflake and Python; support data integration, modeling, and ETL/ELT development. · Prepare, clean, and validate data for AI connectors and help build reusable data products, including curated datasets and documented views. · Assist in building AI/GenAI applications using LLMs, APIs, and retrieval-based approaches, with exposure to relational, graph, and vector data technologies. · Collaborate on development, testing, debugging, and documentation. Use approved AI coding tools while understanding and validating generated code and outputs. · Follow Firm requirements for confidentiality, data access, and approved AI use; escalate data-quality or technical issues when guidance is needed.
Required Skills: · Python: Hands-on experience with data processing, automation, Pandas, and basic API integration. · SQL & Snowflake: Practical exposure to SQL queries, tables and views, data transformations, and ETL/ELT concepts. · AI / GenAI: Basic understanding of LLMs, prompting, retrieval-augmented generation (RAG), embeddings, and vector search. · Development Fundamentals: Familiarity with REST APIs, Git, JSON, testing, and documentation. · Strong attention to detail, analytical thinking, communication, and willingness to learn and seek guidance.
Nice to Haves: · Exposure to graph data models, knowledge graphs, Neo4j, Cypher, or similar technologies. · Exposure to LangChain, LlamaIndex, Snowpark, Snowflake Cortex AI, or other cloud AI services. · Familiarity with AWS, Azure, or GCP and AI-assisted coding tools such as GitHub Copilot. Education & Experience: · Bachelor's degree in a relevant technical field or equivalent practical experience. · 0–2 years of relevant experience, including internships or academic projects. Strong fundamentals and practical project experience are valued over expertise in every listed technology.
Key Responsibilities: · Develop and maintain data pipelines, SQL queries, and transformations using Snowflake and Python; support data integration, modeling, and ETL/ELT development. · Prepare, clean, and validate data for AI connectors and help build reusable data products, including curated datasets and documented views. · Assist in building AI/GenAI applications using LLMs, APIs, and retrieval-based approaches, with exposure to relational, graph, and vector data technologies. · Collaborate on development, testing, debugging, and documentation. Use approved AI coding tools while understanding and validating generated code and outputs. · Follow Firm requirements for confidentiality, data access, and approved AI use; escalate data-quality or technical issues when guidance is needed.
Required Skills: · Python: Hands-on experience with data processing, automation, Pandas, and basic API integration. · SQL & Snowflake: Practical exposure to SQL queries, tables and views, data transformations, and ETL/ELT concepts. · AI / GenAI: Basic understanding of LLMs, prompting, retrieval-augmented generation (RAG), embeddings, and vector search. · Development Fundamentals: Familiarity with REST APIs, Git, JSON, testing, and documentation. · Strong attention to detail, analytical thinking, communication, and willingness to learn and seek guidance.
Nice to Haves: · Exposure to graph data models, knowledge graphs, Neo4j, Cypher, or similar technologies. · Exposure to LangChain, LlamaIndex, Snowpark, Snowflake Cortex AI, or other cloud AI services. · Familiarity with AWS, Azure, or GCP and AI-assisted coding tools such as GitHub Copilot. Education & Experience: · Bachelor's degree in a relevant technical field or equivalent practical experience. · 0–2 years of relevant experience, including internships or academic projects. Strong fundamentals and practical project experience are valued over expertise in every listed technology.