AI-Ready Data Engineer (AWS & Ingestion Pipelines)

RADcube; Indianapolis (IN); On-site; USD 110,000 - 140,000; Full time

Job summary

RADcube in Indianapolis, IN is seeking a Data Engineer – AWS to design ingestion pipelines feeding analytics and AI/GenAI use cases. You will ingest structured and unstructured data from multiple sources into the AWS data lake and prepare AI-ready datasets with document parsing, chunking and embedding pipelines.

Ideal candidates have 4+ years in data engineering, strong AWS (Glue, S3, Lambda, Step Functions, Kinesis) experience and Python/PySpark, with nice-to-have Bedrock, vector databases, and

Qualifications

• Must have: 4+ yrs, AWS (Glue, S3, Lambda, Step Functions, Kinesis), Python, PySpark.
• Nice to have: Bedrock, vector databases, OpenSearch

Responsibilities

• Design ingestion pipelines feeding analytics and AI/GenAI use cases.
• Ingest structured and unstructured data from multiple sources into the AWS data lake.
• Prepare AI-ready datasets, including document parsing, chunking and embedding pipelines

Skills

Data engineering

AWS experience

Python

PySpark

Tools

AWS (Glue, S3, Lambda, Step Functions, Kinesis)

Python

PySpark

Bedrock

vector databases

OpenSearch

Job description

RADcube in Indianapolis, IN is seeking a Data Engineer – AWS to design ingestion pipelines feeding analytics and AI/GenAI use cases. You will ingest structured and unstructured data from multiple sources into the AWS data lake and prepare AI-ready datasets with document parsing, chunking and embedding pipelines.

Ideal candidates have 4+ years in data engineering, strong AWS (Glue, S3, Lambda, Step Functions, Kinesis) experience and Python/PySpark, with nice-to-have Bedrock, vector databases, and