Job Summary:
We are seeking an experienced Data Engineer to design, develop, and optimize scalable data pipelines and cloud-based data solutions using GCP, Vertex AI, and Gemini.

Key Responsibilities:

• Design and develop modular, reusable data solutions using Python and strong OOP practices.
• Build and optimize ETL/ELT pipelines using BigQuery, Cloud Dataflow, Cloud Composer/Airflow, Pub/Sub, Cloud Functions, and Cloud Run.
• Develop real-time and event-driven data processing architectures.
• Design data warehouses, schemas, partitioning, clustering, and materialized views.
• Build and integrate REST APIs and external data sources, including APIs and flat files.
• Use Docker and Kubernetes for containerized applications and workloads.
• Implement CI/CD using Git, Cloud Build, GitHub Actions, and Jenkins.
• Monitor applications and pipelines using Cloud Monitoring, Cloud Logging, and Error Reporting.
• Implement IAM, access controls, data governance, and automated CVE remediation.
• Leverage Gemini, Vertex AI, and AI-assisted development tools such as GitHub Copilot.
• Collaborate with Agile/SAFe teams using Jira and participate in integration and functional testing.

Required Skills:

• 8+ years of Data Engineering experience.
• Strong Python programming and OOP experience.
• Hands-on GCP experience with BigQuery, Cloud Storage, Dataflow, Cloud Composer/Airflow, Pub/Sub, Cloud Functions, and Cloud Run.
• Strong ETL/ELT, data pipeline, streaming, and data warehousing experience.
• Experience with Docker, Kubernetes, REST APIs, and CI/CD.
• Experience with Vertex AI and Gemini.
• Knowledge of cloud security, IAM, data governance, and observability.
• Experience with Agile/SAFe delivery practices and Jira.

Preferred:

• GitHub Copilot or other AI-assisted development experience.
• Integration and functional testing experience.
• Exposure to AWS or Azure.