Description

8 to 12 years of experience in Data Engineering, Big Data, and Cloud Data Platforms. Strong hands-on experience with Google Cloud Platform (GCP). Expertise in BigQuery for data warehousing, analytics, and performance optimization. Strong experience with Dataflow and Apache Beam for large-scale data processing. Experience with Apache Airflow and/or Cloud Composer for workflow orchestration. Hands-on experience with Cloud Spanner and distributed database concepts. Strong programming skills in Python and SQL. Experience building enterprise-grade ETL/ELT pipelines. Knowledge of Pub/Sub, Cloud Storage, Cloud Functions, and other GCP services. Strong understanding of data modeling, performance tuning, and data integration. Experience with version control systems such as Git. Knowledge of CI/CD, DevOps practices, and Agile methodologies.

Design, develop, and maintain enterprise-scale data engineering solutions on Google Cloud Platform (GCP). Build scalable ETL/ELT pipelines using Dataflow, Apache Beam, BigQuery, and Cloud Composer (Airflow). Design and optimize BigQuery data warehouses for large-scale analytics and reporting. Develop batch and real-time data pipelines using Dataflow and GCP-native services. Implement workflow orchestration using Apache Airflow / Cloud Composer. Design and manage data models and schemas in Cloud Spanner and BigQuery environments. Integrate multiple data sources using GCP services such as Pub/Sub, Cloud Storage, Cloud Functions, and Dataflow. Monitor, troubleshoot, and optimize pipeline performance, reliability, and scalability. Collaborate with architects, business stakeholders, and development teams to deliver cloud data

Key Skills

Education

Bachelor's degree