Roles and Responsibilities

• Design, build, and deploy scalable and reliable data applications using Google Cloud Platform services.
• Develop ETL/ELT pipelines and data workflows leveraging BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer, Cloud Run, and Dataproc.
• Write efficient SQL queries and Python scripts to process, transform, and analyze large datasets.
• Set up and configure cloud infrastructure components for data engineering solutions.
• Automate deployment and integration pipelines using CI/CD best practices.
• Ensure the security and compliance of cloud applications and data.
• Diagnose and resolve technical issues related to cloud data solutions.
• Optimize applications and infrastructure for performance, reliability, and cost-efficiency.

Required Skills & Qualifications

• 5 to 7 years of total professional experience, with a minimum of 5 years working on Google Cloud Platform and Python development.
• Strong proficiency in SQL and Python programming.
• In-depth understanding of data warehousing concepts and experience with BigQuery.
• Hands-on experience with GCP services including: BigQuery, Dataflow, Pub/Sub, Cloud Storage, Cloud Composer, Cloud Run, Dataproc.
• Experience in building and deploying scalable cloud-native applications.
• Familiarity with CI/CD pipelines and automation tools.
• Strong problem-solving skills and ability to troubleshoot complex cloud environments.
• Knowledge of cloud security best practices.

Preferred Qualifications

• Certifications related to Google Cloud Platform (e.g., Google Professional Data Engineer).
• Experience working in Agile teams.
• Exposure to containerization (e.g., Docker, Kubernetes).

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