Data Engineer - Google Cloud Platform

<p><b>Key Responsibilities :</b><br/><br/>- Design, develop, and maintain scalable data pipelines using GCP services such as Cloud Storage, BigQuery, Composer, DataProc, and Pub/Sub.<br/><br/>- Work with both SQL and NoSQL databases for data extraction, transformation, and analysis.<br/><br/>- Develop and optimize Python scripts for data processing, automation, and workflow orchestration.<br/><br/>- Implement and manage data lake architectures, ensuring proper governance, lifecycle management, and cost optimization.<br/><br/>- Collaborate with cross-functional teams (data science, analytics, product, engineering) to deliver reliable, cloud-based data solutions.<br/><br/>- Apply best practices in ETL processes, cloud data architecture, and data quality frameworks.<br/><br/><b>Required Skills :</b><br/><br/>- Strong hands-on experience with GCP data services: BigQuery, Pub/Sub, DataProc, Composer, Cloud Storage.<br/><br/>- Proficiency in Python for data processing and automation.<br/><br/>- Strong understanding of ETL pipelines and data warehousing concepts.<br/><br/>- Experience with SQL (query optimization, schema design) and exposure to NoSQL databases (e.g., MongoDB, Bigtable, Cassandra).<br/><br/>- Knowledge of data lake design, governance, and lifecycle management.<br/><br/>- Familiarity with CI/CD, version control (Git), and modern data workflows.<br/><br/><b>Good to Have :</b><br/><br/>- Experience with streaming data pipelines.<br/><br/>- Exposure to data modeling and metadata management.<br/><br/>- Knowledge of data security and compliance best practices.<br/><br/>- Google Cloud Professional Data Engineer Certification.<br/><br/>Education :<br/><br/>- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.</p> (ref:hirist.tech)