AI Data Engineer

Apptad Inc.
Memphis, TN, United States
23 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Compensation
$95,000.0 - $125,000.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Airflow Microsoft Azure Continuous Integration Data Cleansing Data Dictionary Information Engineering Data Governance Extract Transform Load (ETL) Data Warehousing DevOps Data Flow Control
+24 more
Python (Programming Language) Machine Learning NoSQL Search Technologies SQL Databases Unstructured Data Informatica Powercenter Retrieval-Augmented Generation Large Language Models Prompt Engineering Apache Spark Generative AI Git Containerization Data Lakes Pyspark Kubernetes Deployment Automation Star Schema Data Management Restful APIs 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

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.careerjet.com

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:03 min

Career evolution in data engineering and AI platforms

Maria Apazoglou · Coffee With Developers

6:21 min

Investigating push inefficiencies with upstream Git experts

Jonathan Creamer · Coffee With Developers

2:37 min

Comparing traditional SQL tables versus NoSQL non-tabular databases

Stanimira Vlaeva · JS Congress

2:17 min

Mapping the maturity roadmap for scaled devops adoption

Dominik Krichbaum Dominik Krichbaum · WWC Europe 2026

2:08 min

Essential engineering roles in the generative AI space

Mary Grygleski Mary Grygleski · LIVE

56 sec

Favorite git commands and the importance of patch commits

Eileen Uchitelle Eileen Uchitelle +1 · Coffee With Developers

Videos

See all

Related articles

See all