Job 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
