<p><p><b>About the Role :</b><br/><br/>We are seeking experienced Google Cloud Platform (GCP) Engineers to join our team in building a scalable and robust Model Monitoring Framework.
</p><p><br/></p><p>This solution will integrate data from diverse sources including Excel files, SAS datasets, and GCP-native services, with the target architecture fully hosted on Google Cloud Platform.<br/><br/><b>Key Responsibilities :</b><br/><br/>- Design and develop end-to-end ETL pipelines to ingest, transform, and load data from on-premises SAS systems, Excel files, and GCP sources.<br/><br/>- Build scalable and secure data ingestion frameworks using GCP services such as Cloud Storage, BigQuery, Cloud Functions, and Dataflow.<br/><br/>- Collaborate with data scientists and analysts to enable model monitoring, including drift detection, performance tracking, and alerting.<br/><br/>- Implement data validation, quality checks, and audit trails across the pipeline.<br/><br/>- Optimize pipeline performance and cost using GCP-native tools and best practices.<br/><br/>- Automate workflows using Cloud Composer (Airflow) or Cloud Scheduler.<br/><br/>- Ensure compliance with data governance, security, and privacy standards.<br/><br/><b>Required Skills & Qualifications</b><br/><br/>- 4+ years of experience in cloud engineering, with at least 2 years on GCP.<br/><br/>- Strong proficiency in Python, SQL, and data engineering frameworks.<br/><br/>- Hands-on experience with BigQuery, Cloud Storage, Pub/Sub, Dataflow, and Cloud Functions.<br/><br/>- Experience integrating with SAS and handling Excel-based data ingestion.<br/><br/>- Familiarity with model monitoring concepts and ML lifecycle management.<br/><br/>- Knowledge of CI/CD pipelines, Terraform, or Deployment Manager is a plus.<br/><br/>- Excellent problem-solving and communication skills.</p><br/></p> (ref:hirist.tech)