AI Data Engineer
Apptad Inc.
Memphis, United States of America
2 days ago
Role details
Contract type
Temporary to permanent Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
English Compensation
$ 125KJob location
Memphis, United States of America
Tech stack
Artificial Intelligence
Airflow
Azure
Continuous Integration
Data Cleansing
Data Dictionary
Information Engineering
Data Governance
ETL
Data Warehousing
DevOps
Data Flow Control
Python
Machine Learning
NoSQL
Search Technologies
SQL Databases
Unstructured Data
Informatica Powercenter
Retrieval-Augmented Generation
Large Language Models
Prompt Engineering
Spark
Generative AI
GIT
Containerization
Data Lake
PySpark
Kubernetes
Deployment Automation
Star Schema
Data Management
REST
Data Pipelines
Databricks
Microservices
Job description
- 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., Title: Data Engineer Location: Dallas, TX OR Memphis, TN (Hybrid) Duration: 12 months Work Requirements: US Citizen, GC Holders or Authorized to Work in the US Responsibilitie…
- 2 days ago
Requirements
We are seeking an experienced AI Data Engineer (15+ Years) to design, develop, and manage scalable data platforms that enable advanced analytics, Machine Learning (ML), and Generative AI solutions. The ideal candidate will build robust data pipelines, ensure data quality, and integrate AI/ML capabilities into enterprise data ecosystems., * Python, SQL, PySpark
- ETL/ELT development
- Data Modeling (Star Schema, Snowflake Schema)
- Apache Spark, Databricks
- Airflow, Dataflow, Informatica, ADF, Synapse, or equivalent tools
- Relational & NoSQL Databases
- Data Warehousing concepts
- REST APIs and Microservices
- Git, CI/CD, DevOps practices
AI & GenAI 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