GCP Data Engineer (Python & PySpark)

Job Description We are looking for a GCP Data Engineer with strong expertise in Python and PySpark to join our team. The ideal candidate will have hands-on experience in building scalable ETL/ELT pipelines, processing large datasets, and working with Google Cloud Platform (GCP) services. The candidate should possess excellent communication skills and be available to join immediately . Mandatory Skills - Google Cloud Platform (GCP) - Python - PySpark - ETL/ELT Pipeline Development - BigQuery - Google Cloud Storage (GCS) - SQL - Data Engineering concepts Key Responsibilities - Design, develop, and maintain scalable ETL/ELT data pipelines on GCP. - Develop data processing solutions using Python and PySpark . - Build and optimize data pipelines using BigQuery , GCS , and other GCP services. - Write efficient SQL queries for data extraction, transformation, and analysis. - Process structured and semi-structured data from multiple sources. - Monitor, troubleshoot, and optimize data pipelines for performance and reliability. - Collaborate with cross-functional teams to understand business requirements and deliver data solutions. - Ensure data quality, security, and governance across data platforms. - Support deployment, automation, and operational activities within GCP environments. Required Experience - 4+ years of experience in Data Engineering. - Hands-on experience with Google Cloud Platform (GCP) . - Strong programming experience in Python and PySpark . - Experience working with BigQuery , Google Cloud Storage (GCS) , and SQL. - Good understanding of data warehousing and ETL concepts. - Experience in performance tuning and optimization of data pipelines. Preferred Skills - Experience with Dataproc, Airflow, Pub/Sub, or Cloud Composer. - Knowledge of Spark SQL and DataFrames. - Familiarity with CI/CD and version control tools. - Experience working in Agile environments. Skills: Pyspark, Python Experience: 6.00-10.00 Years