Description

Design, develop, and maintain scalable ETL/ELT pipelines using PySpark, Airflow, and GCP-native tools.
Build and optimize data warehouses and analytics solutions in BigQuery.
Implement and manage workflow orchestration with Airflow/Cloud Composer.
Write complex SQL queries for data transformations, analytics, and performance optimization.
Ensure data reliability, security, and governance across pipelines.
Conduct performance tuning and cost optimization of BigQuery and PySpark workloads.
Collaborate with analysts and product teams to deliver reliable data solutions.
Troubleshoot, debug, and resolve production issues in large-scale data pipelines.
Contribute to best practices, reusable frameworks, and automation for data engineering.5+ years of experience within Data Engineering/ Data Warehousing using Big Data technologies will be a addon
Expert on Distributed ecosystem
Hands-on experience with programming using Python
Expert on Hadoop and Spark Architecture and its working principle
Hands-on experience on writing and understanding complex SQL(Hive/PySpark-dataframes),
optimizing joins while processing huge amount of data

Key Skills

Education

Bachelor's degree