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