Junior Data & AI Engineer
PRI Technology
New York City Metropolitan Area0–2 yrs2h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 2 years · Bachelor's degree
- Must know
- ETLSQLSnowflakePythonREST APIsLLMs
- Work
- On-site in New York City Metropolitan Area
- Pay
- Not stated by the employer.
- Skill demand
- Python76%SQL64%ETL46%Snowflake15%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 2, 2026 · still open
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About the Role
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.
Requirements & Tech Stack
- 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.
Qualifications
- Bachelor's degree in a relevant technical field or equivalent practical experience.
- 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.