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.