Description

You will design, develop, and optimize large-scale data pipelines using PySpark and Python.

This role is hybrid.

Responsibilities

• Build scalable data transformations and ETL workflows using PySpark and Python.
• Write and optimize complex SQL queries for data extraction and loading.
• Implement object-oriented programming principles to ensure code maintainability.
• Troubleshoot data issues and perform performance tuning on data jobs.
• Collaborate with data scientists and stakeholders to translate requirements into technical solutions.

Required Skills

• 5+ years of experience in data engineering or backend development.
• Strong hands-on expertise with PySpark and Python.
• Proficient in SQL with a focus on query optimization.
• Experience with AWS services: S3, Glue, EMR, Redshift, Lambda.
• Working knowledge of Kafka for data streaming.
• Solid understanding of OOP principles and design patterns.
• Experience using AI tools in development workflows.

Preferred Skills

• Experience building cloud-native data workflows on AWS.
• Experience participating in code reviews and data quality checks.

Key Skills

Education

Bachelor's degree