- Strong expertise in Google Cloud Platform (GCP) architecture and data services, with proven experience designing and deploying large-scale enterprise data solutions.

- Experience and learnings using GCP core services such as Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud Functions.

- Deep expertise in BigQuery, including data modeling, schema design, performance tuning, and building data pipelines for large-scale analytics.

- Hands-on experience deploying and managing scalable data solutions in production on GCP.

- Proficiency in Infrastructure as Code (IaC) languages, such as Terraform (Must), with a focus on creating reusable and modular configurations for data infrastructure.

- Deep understanding of cloud-native data concepts, including data warehousing, data lakes, ETL/ELT processes, and building analytical systems.

- Experience with CI/CD pipelines and GitOps for automated build, test, and deployment of data workflows on GCP.

- Strong problem-solving skills and the ability to translate complex business requirements into practical and scalable data solutions.

- Strong communication and collaboration skills to work effectively in interdisciplinary teams.

Preferred Additional Skills :

- Google Cloud Professional Data Engineer or Architect certification.

- Publications or open-source contributions in data architecture, data engineering, or related fields.

- Familiarity with emerging AI platforms and frameworks, such as Agent Space.