Description

Build and maintain scalable data pipelines and APIs using Python and PySpark on Google Cloud Platform.

This role is on-site.

Responsibilities

• Design and develop batch and real-time data pipelines using PySpark on distributed clusters.
• Build secure, scalable Python APIs using FastAPI or Flask.
• Implement and manage GCP services including BigQuery, Composer, DAGs, and Cloud Storage.
• Establish data quality checks, validations, and monitoring frameworks within pipelines.
• Collaborate with data analysts, BI teams, and platform engineers to ensure reliability and performance.

Required Skills

• 5+ years of hands-on experience with PySpark and distributed computing.
• Strong proficiency in Python for building scalable APIs (FastAPI/Flask).
• Deep knowledge of Google Cloud Platform services: BigQuery, Composer, Cloud Storage.
• Experience designing robust batch and/or real-time data pipelines.
• Understanding of data quality frameworks and best practices.
• Any Graduate degree.

Preferred Skills

• Experience with BI tools like Power BI or MicroStrategy.
• Familiarity with CI/CD pipelines and DevOps practices.

Key Skills

Education

Any Gradute