Cynet Systems

AI Data Engineer - Remote / Telecommute

Nashville, TN (Remote) · Posted 3w ago

salary not listedcontractremote
PythonSQLPySparkApache SparkDatabricksAirflowDataflowInformaticaADFSynapseNoSQLREST APIsGitCI/CDPineconeChromaDBFAISSOpenAIAzure OpenAIGeminiClaude

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.