Python, PySpark, ETL Developer
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Python, PySpark, ETL Developer

Date Posted
13 July 2026
Location
Hyderabad
Positions
1
Views
1
Employment Information
Open Positions
1
Location
Hyderabad
Address
Hyderabad
Experience
3 Years
Functional Area
Design
Job Description

Role: Python, PySpark, ETL Developer

Industry Type: IT Services & Consulting

Department: Engineering - Software & QA

Employment Type: Full Time, Permanent

Role Category: DBA / Data warehousing

UG: Any Graduate

PG: Any Postgraduate

Educational Requirements

Bachelor of Engineering
Service Line
Data Analytics Unit
Responsibilities
  • Data Pipeline DevelopmentDevelop and maintain scalable batch ETL pipelines using Python and PySpark for data ingestion, transformation, and loading.
  • Implement reusable transformation logic, ensuring pipelines are modular, testable, and easy to maintain.
  • Optimize Spark jobs for performance (partitioning, caching, joins, shuffles) and cost efficiency.
  • Data Quality Reliability: Apply data validation checks, handle schema evolution, and ensure accuracy and completeness of processed datasets.
  • Troubleshoot pipeline failures, analyze logs, and implement robust error handling and retry mechanisms.
  • Monitor job runs and support operational stability through alerts, runbooks, and timely incident resolution.
  • Collaboration Delivery: Work with cross-functional teams to gather requirements, define data mappings, and deliver datasets aligned to business needs.
  • Participate in code reviews, follow engineering best practices, and contribute to continuous improvement of standards and tooling.
  • Document pipeline logic, dependencies, and operational procedures for smooth handovers and long-term maintainability.
Additional Responsibilities:
Bachelors degree in Computer Science, Engineering, Information Systems, or a related field (or equivalent practical experience).
25 years of hands-on experience building data pipelines using Python and PySpark.
Strong understanding of ETL concepts, data transformations, and handling large-scale datasets.
Proficiency in writing clean, maintainable code and debugging production issues.
Working knowledge of data structures, algorithms, and software development best practices.
Technical and Professional Requirements:
Technology - Analytics - Packages - Python - Big Data, Technology - Big Data - Data Processing - PySpark, ETL
Preferred Skills:
Technology - Analytics - Packages - Python - Big Data
Technology - Big Data - Data Processing - PySpark

Skills & Tags
Skills
GoPython
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