Description

You will design and build ETL/ELT pipelines, data processing workflows, and GenAI architectures including RAG pipelines and vector indexing.

This role is on-site.

Responsibilities

• Develop batch and real-time data pipelines using Apache Spark and Kafka.
• Implement GenAI data architectures, including RAG pipelines and vector indexing.
• Manage and optimize Vector Databases for embedding storage and similarity search.
• Build secure data solutions on AWS (S3, Glue, Redshift) ensuring data quality and compliance.
• Support analytics, reporting, and data modernization initiatives using Databricks or Snowflake.

Required Skills

• 5+ years of experience in data engineering or related roles.
• Strong proficiency in Python and SQL.
• Experience with AWS services: S3, Glue, Redshift.
• Hands-on experience with ETL/ELT and data pipelines.
• Mandatory experience with Vector Databases.
• Mandatory experience with GenAI / LLM frameworks (LangChain or LangGraph).
• Experience with Big Data frameworks (Apache Spark, Apache Kafka).
• Workflow orchestration using Apache Airflow.
• Experience with data platforms like Databricks or Snowflake.

Preferred Skills

• Master's degree in a relevant field.

Key Skills

Education

Bachelor's or Master's degrees