Haystack
← Back to Jobs
Technology
SI

AWS GenAI Data Engineer

StratEdge It consulting INCCharlotte, NC🇺🇸United StatesPosted 12 Aug 2026

Why This Role Stands Out

This role offers a fantastic opportunity to build cutting-edge GenAI data foundations on AWS, working with a leading client and leveraging advanced AI tools. You'll thrive here if you have a strong background in data engineering with significant AWS and GenAI experience, and you're eager to push the boundaries of AI development. Apply now to gain valuable experience and advance your career in this dynamic field.

Quick Overview

Salary
$60 - $65/hr
Work Type
On Site
Level
Mid Senior

Job Description

Location: Charlotte, NC

Work Arrangement: Hybrid/Onsite - Charlotte, NC

Client: Cognizant

Employment Type: W2

Billing Rate: $60-$65/hr W2

Visa: Any visa status is acceptable

Job Summary

We are seeking an experienced AWS GenAI Data Engineer to design, build, and optimize scalable data foundations supporting Machine Learning, Generative AI, LLM, and Agentic AI use cases.

AWS Gen AI data engineer -

Experience: 5+ years of professional experience in data engineering, with at least 2+ years explicitly focused on designing data foundations for ML and Generative AI use cases.

Cloud Expertise (AWS): Deep, hands-on expertise with core AWS data and AI services, including Amazon Bedrock, Amazon Bedrock Agent Core, Amazon QuickSuite, S3, AWS Glue, EMR, Athena, IAM, and Lambda.

GenAI & Vector Tooling: Practical familiarity with LLMs, prompt patterns, embeddings, vector databases (e.g., OpenSearch Serverless, Pinecone, or PostgreSQL with pgvector), and RAG frameworks.

Agentic Frameworks & Specialized Delivery Agents: Hands-on experience with multi-agent orchestration via ASTRA, project/SDLC automation through AIFlow Apex, database migration automation using Proserve DBM Apex, and ETL modernisation via Apex Delivery Agent (Informatica to AWS Glue).

AI-Assisted Engineering: Experience utilizing developer tools and frameworks like Kiro for accelerated pipeline building, debugging, and automated code generation.

Programming & Frameworks: Advanced proficiency in Python and SQL, alongside distributed data processing frameworks like PySpark or Databricks.

Orchestration & DevOps: Hands-on experience with workflow orchestrators (Airflow) and CI/CD automation pipelines (GitHub Actions, GitLab, or AWS CodePipeline).

Skills

SQL
AWS
ETL
Machine Learning
Airflow
Databricks
Generative AI
GitHub Actions
LLM
PostgreSQL
Python

Similar jobs