Data Engineer PySpark Snowflake AWS And GenAI

D4 Insight; Hyderabad; On-site; INR 450,000 - 800,000; Full time

Job summary

D4 Insight in Hyderabad, India, is seeking an experienced Data Engineer to design and maintain scalable data pipelines using SQL, PySpark, Python, and Snowflake. You will implement Medallion Architecture across Bronze, Silver, and Gold layers and build reusable engineering frameworks for efficient processing.

You will also develop ingestion pipelines with AWS Glue/Lambda, stream data with Kafka, and orchestrate workflows with Airflow.

Qualifications

• 6–12 years of relevant data engineering experience.
• Strong hands-on expertise in SQL, PySpark, Python, and Snowflake.
• Experience building scalable data pipelines and reusable engineering frameworks.
• Strong understanding of Medallion Architecture and ETL/ELT processes.
• Hands-on experience with Kafka, AWS Glue, and AWS Lambda.
• Experience with Apache Airflow or other workflow orchestration tools.
• Strong problem-solving skills and a focus on data quality and performance.

Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark, SQL, Python, and Snowflake.
• Build reusable data engineering frameworks for efficient data processing and transformation.
• Implement Medallion Architecture across Bronze, Silver, and Gold layers.
• Develop data ingestion and processing pipelines using AWS Glue and AWS Lambda.
• Implement event-driven and streaming data pipelines using Kafka.
• Orchestrate workflows using Apache Airflow or equivalent tools.
• Optimize SQL queries, Snowflake workloads, and PySpark jobs for performance and scalability.
• Ensure data quality, reliability, and consistency across pipelines.
• Explore GenAI-based data solutions using LLMs, RAG, and LangChain.

Skills

SQL

PySpark

Python

Medallion Architecture

ETL/ELT

GenAI

Tools

Snowflake

Kafka

Apache Airflow

AWS Glue

AWS Lambda

Job description

Job Description:

Location: Hyderabad, India

Experience: 6–12 Years

Role Overview

We are looking for experienced Data Engineer with strong expertise in SQL, PySpark, Python, and Snowflake to design and maintain scalable data pipelines and engineering frameworks. The role involves cloud data services, Medallion Architecture, ETL/ELT workflows, and orchestration, with exposure to GenAI technologies as an added advantage.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines using PySpark, SQL, Python, and Snowflake.
• Build reusable data engineering frameworks for efficient data processing and transformation.
• Implement Medallion Architecture across Bronze, Silver, and Gold layers.
• Develop data ingestion and processing pipelines using AWS Glue and AWS Lambda.
• Implement event-driven and streaming data pipelines using Kafka.
• Orchestrate workflows using Apache Airflow or equivalent tools.
• Optimize SQL queries, Snowflake workloads, and PySpark jobs for performance and scalability.
• Ensure data quality, reliability, and consistency across pipelines.
• Explore GenAI-based data solutions using LLMs, RAG, and LangChain.

Required Skills & Experience

• 6–12 years of relevant data engineering experience.
• Strong hands‑on expertise in SQL, PySpark, Python, and Snowflake.
• Experience building scalable data pipelines and reusable engineering frameworks.
• Strong understanding of Medallion Architecture and ETL/ELT processes.
• Hands‑on experience with Kafka, AWS Glue, and AWS Lambda.
• Experience with Apache Airflow or other workflow orchestration tools.
• Strong problem‑solving skills and a focus on data quality and performance.

Good to Have: GCP, additional AWS services, MCP (Model Context Protocol), LLMs, RAG, and LangChain.