Job Summary
Key Responsibilities
- Design, build, and maintain data engineering solutions on Google Cloud Platform (GCP).
- Develop and manage data pipelines using Python and SQL.
- Work with GCS Buckets, Firestore DB, Cloud Functions, and Cloud Scheduler for data processing and automation.
- Build and integrate APIs and MCP-based solutions as per business requirements.
- Implement and manage messaging solutions using Pub/Sub.
- Use GitHub Actions for CI/CD and deployment automation.
- Support forward deployable applications and ensure smooth production releases.
- Collaborate with stakeholders to understand requirements and define data strategy through discussions.
- Work closely with QA teams to ensure data quality, validation, and testing.
- Proactively follow up on open questions and provide solutions, not just execute tasks.
- Communicate clearly with team members and stakeholders on progress, risks, and dependencies.
Skill Requirements
6+ Strong experience in GCP Data Engineering technologies.
5+ Years of expertise in Python and SQL.
5+ Experience with Cloud Functions, GCS Buckets, Firestore DB, Cloud Scheduler, and Artifact Registry.
3+ Experience in API development and MCP-based architectures.
3+ Experinaceof Pub/Sub messaging systems.
3+ experience with GitHub Actions for CI/CD pipelines.
Experiance forward deployable applications.
Ability to gather requirements and define strategy through conversations.
Understanding of QA processes and data validation practices.
Other Requirements
1.Google Cloud Professional Data Engineer certification is preferred.