Description

Build and maintain scalable data pipelines and warehouses using PySpark, Airflow, and GCP.

This role is on-site.

Responsibilities

• Design and maintain ETL/ELT pipelines using PySpark, Airflow, and GCP-native tools.
• Build and optimize data warehouses and analytics solutions in BigQuery.
• Implement workflow orchestration with Airflow and Cloud Composer.
• Write complex SQL for data transformations, analytics, and performance tuning.
• Troubleshoot production issues and ensure data reliability, security, and governance.

Required Skills

• 5+ years of experience in Data Engineering or Data Warehousing.
• Expert-level knowledge of Hadoop and Spark architecture.
• Hands-on programming experience with Python.
• Proficiency in writing and optimizing complex SQL (Hive/PySpark DataFrames).
• Experience with distributed ecosystems and large-scale data processing.
• Ability to optimize joins and performance for huge datasets.
• Bachelor's degree in a relevant field.

Key Skills

Education

Bachelor's degree