Data Engineer With GenAI

Broadmind Designs LLC

Dallas, TX, United States

about 1 month ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

10 years minimum

Compensation

$118,386.0 - $142,572.0

Working hours

Regular working hours

Job source

www.indeed.com

Tech stack

Artificial Intelligence Amazon Web Services Software Applications Microsoft Azure Cloud Computing Continuous Integration Information Engineering Data Integration Extract Transform Load (ETL) Data Systems Data Warehousing Python (Programming Language)

+22 more

Search Technologies SQL Databases Data Streaming Enterprise Data Management Data Processing Enterprise Software Applications Azure Data Factory Large Language Models Prompt Engineering Apache Spark Generative AI Git Build Management AI Platforms Kubernetes HuggingFace Data Management Restful APIs Data Pipelines Automation Anywhere Docker Databricks

Job description

We are looking for an experienced Data Engineer with Generative AI experience to design and build scalable data pipelines and AI-powered data solutions. The ideal candidate should have strong expertise in Python, SQL, Spark, Databricks, ETL/ELT, Cloud Platforms, and Generative AI technologies. You will work closely with Data Scientists, AI Engineers, and Business Teams to develop data platforms, integrate Large Language Models (LLMs), build RAG applications, and deliver production-ready AI solutions., * Design, develop, and maintain scalable ETL/ELT data pipelines using Python, SQL, and Spark.

Build and optimize data processing solutions using Databricks, Azure Data Factory, or similar tools.
Develop and maintain data lakes, data warehouses, and enterprise data platforms.
Build AI-powered applications using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
Develop AI workflows using LangChain, LangGraph, LlamaIndex, or similar frameworks.
Integrate OpenAI, Azure OpenAI, AWS Bedrock, or Hugging Face models into enterprise applications.
Work with vector databases such as Pinecone, FAISS, or ChromaDB for semantic search and AI solutions.
Optimize data pipelines, SQL queries, and Spark jobs for performance and scalability.
Build proof-of-concept (POC) solutions and evaluate new AI tools, models, and frameworks.
Collaborate with Data Scientists, AI Engineers, Product Owners, and Business Teams to deliver AI-driven data solutions.
Develop REST APIs and integrate AI services into enterprise applications.
Support CI/CD pipelines, automation, deployment, monitoring, and production support.
Document technical designs, data flows, and implementation processes.

Requirements

10+ years of experience in Data Engineering.
Strong experience with Python, SQL, Spark, and Databricks.
Experience building ETL/ELT pipelines and data integration solutions.
Hands-on experience with Azure, AWS, or GCP cloud platforms.
Experience with Generative AI, Large Language Models (LLMs), Prompt Engineering, and RAG.
Experience with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
Experience with OpenAI, Azure OpenAI, AWS Bedrock, Anthropic, or Hugging Face.
Knowledge of Vector Databases such as Pinecone, FAISS, or ChromaDB.
Experience with REST APIs, Git, Docker, Kubernetes, and CI/CD.
Strong communication, analytical, and problem-solving skills.