AI Data Engineer - Remote / Telecommute
Why This Role Stands Out
This remote AI Data Engineer role offers a fantastic opportunity to work with cutting-edge AI and LLM technologies, fostering significant career growth and skill development. You'll thrive here if you have a strong foundation in Python, SQL, PySpark, and ETL/ELT, while enjoying the flexibility of a telecommute position. Apply now to join a dynamic team and contribute to innovative data solutions!
Quick Overview
Job Description
We are looking for AI Data Engineer - Remote / Telecommute for our client in Nashville TN.
Job Title: AI Data Engineer - Remote / Telecommute
Job Location: Nashville TN
Job Type: Contract
Job Overview:
Requirement/Must Have:
- 1+ years of experience in Python, SQL, and PySpark.
- Experience in ETL/ELT development.
- Knowledge of Data Modeling (Star Schema, Snowflake Schema).
- Familiarity with Apache Spark and Databricks.
- Experience with Airflow, Dataflow, Informatica, ADF, Synapse, or equivalent tools.
- Understanding of Relational & NoSQL Databases.
- Knowledge of Data Warehousing concepts.
- Experience with REST APIs and Microservices.
- Familiarity with Git, CI/CD, and DevOps practices.
Responsibilities:
- Design, develop, and maintain scalable ETL/ELT pipelines for structured and unstructured data.
- Build and optimize data lakes, data warehouses, and AI-ready data platforms.
- Develop ingestion, transformation, and orchestration frameworks using cloud-native technologies.
- Prepare, cleanse, and engineer datasets for AI/ML and Generative AI workloads.
- Integrate Large Language Models (LLMs), vector databases, embeddings, and RAG (Retrieval-Augmented Generation) pipelines into enterprise solutions.
- Implement data governance, security, lineage, and quality controls.
- Collaborate with Data Scientists, AI Engineers, Business Analysts, and Solution Architects.
- Monitor, troubleshoot, and optimize data pipelines and platform performance.
- Automate deployment, testing, and monitoring of data engineering workflows.
- Create technical documentation and data dictionaries for enterprise data assets.
Skills:
- Machine Learning fundamentals.
- Data preparation for AI models.
- Vector Databases (Pinecone, ChromaDB, FAISS).
- LLM Integration (OpenAI, Azure OpenAI, Gemini, Claude, etc.).
- RAG Architecture.
- Embeddings and Semantic Search.
- Prompt Engineering fundamentals.
Skills
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