Data Engineer Experienced

Data Engineer -

AI Platforms, Data Engineering

Pay Rate

$63.00 Per Hour W2

Duration

12 Month Contract

Location

REMOTE

Position Details

• Work Arrangement: 100% Remote
• Business Hours: 9-5pm EST
• Extension and/or Conversion Opportunity: Yes.

Qualifications

• Strong SQL + one of Python/Scala for pipeline development, experience with orchestration tools and understanding of AI models.

Deal Breakers

• Strong sql + Python understanding, AI data skills and API implementation.

Specific systems, tools, or technologies

• Snowflake, dbt, Python

Minimum Education Requirement

Masters or undergrad with relevant experience

Minimum Experience Requirement

6 years

Additional Insights

• Interview Process: 2-3 rounds

Summary

We're looking for a Data Engineer to build and maintain the data infrastructure powering our AI/ML initiatives — including data pipelines for model training, retrieval-augmented generation (RAG), and production ML systems. This role sits at the intersection of data engineering and applied AI, ensuring high-quality, well-governed data is available for both traditional analytics and AI consumption.

Key Responsibilities

• Design and build pipelines to ingest, clean, and transform structured and unstructured data (documents, PDFs, transcripts, logs) for AI/ML use cases
• Build and maintain vector embedding pipelines and support vector database integration
• Develop feature stores/pipelines for ML model training and inference
• Implement data pipelines supporting RAG architectures — chunking strategies, embedding refresh cycles, metadata tagging
• Partner with ML engineers/data scientists to understand data requirements for model training and evaluation
• Ensure data lineage, quality, and governance across pipelines feeding AI systems
• Optimize pipelines for cost and performance (e.g., Dynamic Tables, streaming ingestion)
• Support MLOps/LLMOps workflows — versioning datasets, tracking data used in model training for reproducibility and compliance
• Implement entitlement/access control logic so AI systems only access data they're authorized to use

Required Skills/Experience

• Strong SQL + one of Python/Scala for pipeline development
• Experience with a cloud data platform
• Experience with orchestration tools (Airflow, dbt)
• Understanding of embedding models, vector search, and RAG patterns
• Experience with unstructured data processing
• Familiarity with ML lifecycle concepts

Nice to Have

• Experience with Snowflake Cortex, Cortex Search, or similar in-warehouse AI tooling
• Experience in a regulated industry (financial services) with data entitlement/compliance requirements
• Exposure to LLM application frameworks (LangChain, LlamaIndex)