Description

You will build and optimize large-scale data pipelines using Python and PySpark.

This role is hybrid.

Responsibilities

• Design and implement distributed data processing solutions using PySpark and Python.
• Optimize SQL queries and manage data lake and warehouse architectures.
• Develop robust data engineering workflows with strong OOP and functional programming practices.
• Maintain code quality through version control (Git) and CI/CD integration.

Required Skills

• 8+ years of experience in data engineering or big data processing.
• Expert-level Python skills, including data manipulation, OOP, and functional programming.
• Hands-on experience with PySpark for distributed computing.
• Proficiency in SQL and query optimization techniques.
• Experience with big data platforms such as Hadoop, Hive, or Databricks.
• Familiarity with cloud infrastructure (AWS, Azure, or GCP).
• Solid understanding of data structures, algorithms, and complexity analysis.

Preferred Skills

• Experience with data lake and data warehouse architecture design.
• Strong problem-solving skills with the ability to work independently.

Key Skills

Education

Any Graduate