BigData ,Python and Py Spark , GCP
Roles and Responsibilities:
Develop and maintain data pipelines using BigData processes
Focus on ingesting, storing, processing, and analyzing large datasets
Required skills and qualifications:
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
Experience in UNIX shell scripting Ability to design and develop optimized Data pipelines for batch and real time data processing
Should have experience in analysis, design, development, testing, and implementation of system applications
Demonstrated ability to develop and document technical and functional specifications and analyze software and system processing flows.
Salary Range- $90,000-$110,000 a year