Data Engineer (Pyspark,Python,SQL,ETL)

Role Overview

We are seeking a skilled

Data Engineer

with hands-on experience in

Python, PySpark, and SQL

to design, develop, and maintain scalable data pipelines that support enterprise analytics and reporting. The ideal candidate will have strong experience in data transformation (ETL/ELT), data quality, and working with large datasets in modern data platforms.

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using Python, PySpark, and SQL

Perform data extraction, transformation, and loading from multiple source systems into enterprise data platforms

Develop reusable data transformation logic to support business reporting, analytics, and machine learning initiatives

Optimize SQL queries and PySpark jobs to improve performance and processing efficiency

Build and maintain data models, staging layers, and curated datasets for downstream consumption

Perform data cleansing, validation, reconciliation, and quality checks to ensure data accuracy and consistency

Troubleshoot and resolve data pipeline failures, performance bottlenecks, and data-related issues

Collaborate with business analysts, data architects, and data scientists to understand data requirements and implement scalable solutions

Requirements

Skills required -Python, SQL, Pyspark, ETL

Participate in code reviews, testing, deployment, and production support activities

Develop and maintain technical documentation, including data mappings, transformation logic, and ETL workflows

Ensure compliance with data governance, security, and regulatory standards

Monitor scheduled ETL jobs and proactively address operational issues