AWS GenAI Data Engineer

StratEdge IT Consulting INC; Charlotte (NC); Hybrid; USD 83,000 - 90,000; Full time

Job summary

StratEdge IT Consulting INC is seeking an experienced AWS GenAI Data Engineer to design, build, and optimize scalable data foundations for ML, GenAI, LLM and Agentic AI use cases.

Required expertise includes deep AWS data/AI services (Bedrock, S3, Glue, EMR, Athena, IAM, Lambda) and familiarity with vector databases and multi-agent frameworks like ASTRA and AIFlow Apex. Strong Python/SQL skills with PySpark/Databricks and CI/CD automation are essential.

Qualifications

• 5+ years in data engineering with 2+ in ML/GenAI data foundations.
• Deep hands-on AWS data/AI services expe rience (Bedrock, S3, Glue, EMR, Athena, IAM, Lambda).
• Familiar with LLMs, embeddings, vector databases (OpenSearch Serverless, Pinecone, pgvector).
• Experience with multi-agent orchestration (ASTRA) and AIFlow Apex for SDLC automation.
• ETL modernization via Apex Delivery Agent (Informatica to AWS Glue).
• Proficient in Python and SQL; PySpark/Databricks knowledge.
• Orchestration/DevOps with Airflow and CI/CD (GitHub Actions, GitLab, AWS CodePipeline).

Responsibilities

• Design, build, and optimize scalable data foundations for ML/GenAI use cases.
• Work with GenAI tooling and vector databases in production pipelines.
• Collaborate with data science teams to implement AI-driven data workflows.

Skills

AWS

GenAI

Python

SQL

PySpark

Databricks

Airflow

CI/CD

Vector databases

ETL automation

Tools

Amazon Bedrock

Bedrock Agent Core

Amazon QuickSuite

S3

AWS Glue

EMR

Athena

IAM

Lambda

OpenSearch Serverless

Pinecone

pgvector

ASTRA

AIFlow Apex

Proserve DBM Apex

Apex Delivery Agent

Kiro

PySpark

Databricks

Airflow

GitHub Actions

GitLab

AWS CodePipeline

Informatica

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).