Data Engineer

Randstad

Charlotte, NC, United States

10 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$124,800.0 - $141,440.0

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Amazon S3 Cloud Computing Databases Information Engineering Data Integration Extract Transform Load (ETL) Data Transformation Database Schema Github

+16 more

Python (Programming Language) Liquibase Markdown Management of Software Versions Data Storage Technologies Retrieval-Augmented Generation Large Language Models Prompt Engineering Gitlab Fastapi Pyspark Api Design GPT Software Version Control Data Pipelines Serverless Computing

Job description

Primary Stack (Core Tech)

Language & Processing: Python, PySpark (Handles heavy data transformation and processing)
Cloud (AWS): S3 (Data storage) , Lambda (Serverless code execution) , Glue (Data integration/ETL)
Database Management: Liquibase (Database schema versioning)
API Framework: FastAPI (Exposing processed data to applications)

Secondary Skills

Version Control: GitHub / GitLab
Documentation: Markdown (MD)

Nice-to-Have (The ~10% AI Focus)

RAG (Retrieval-Augmented Generation): Connecting LLMs (like ChatGPT) to internal company databases so the AI gives accurate, company-specific answers.
Prompt Engineering: Crafting effective text prompts to get reliable outputs from AI tools.

Requirements

We are seeking a highly skilled Data Engineer with strong experience in AWS-based data pipelines and modern data engineering practices. The ideal candidate will be hands-on with Python/PySpark, possess solid API development knowledge, and demonstrate proficiency in version control and database change management tools. Experience with AI implementation in data engineering is a strong plus.