Key Responsibilities :

- Design, develop, and maintain scalable data pipelines using GCP services such as Cloud Storage, BigQuery, Composer, DataProc, and Pub/Sub.

- Work with both SQL and NoSQL databases for data extraction, transformation, and analysis.

- Develop and optimize Python scripts for data processing, automation, and workflow orchestration.

- Implement and manage data lake architectures, ensuring proper governance, lifecycle management, and cost optimization.

- Collaborate with cross-functional teams (data science, analytics, product, engineering) to deliver reliable, cloud-based data solutions.

- Apply best practices in ETL processes, cloud data architecture, and data quality frameworks.

Required Skills :

- Strong hands-on experience with GCP data services: BigQuery, Pub/Sub, DataProc, Composer, Cloud Storage.

- Proficiency in Python for data processing and automation.

- Strong understanding of ETL pipelines and data warehousing concepts.

- Experience with SQL (query optimization, schema design) and exposure to NoSQL databases (e.g., MongoDB, Bigtable, Cassandra).

- Knowledge of data lake design, governance, and lifecycle management.

- Familiarity with CI/CD, version control (Git), and modern data workflows.

Good to Have :

- Experience with streaming data pipelines.

- Exposure to data modeling and metadata management.

- Knowledge of data security and compliance best practices.

- Google Cloud Professional Data Engineer Certification.

Education :

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.