Skills

Full description

Design and develop data pipelines using GCP services like BigQuery, Cloud Dataflow, Cloud Function, Composer, Cloud Pub/Sub, and Cloud Storage
Write efficient, scalable, and maintainable Python code for data processing, automation, and integration tasks
Implement ETL/ELT processes to ingest, transform, and store structured and unstructured data
Manage and optimize data storage solutions for performance, cost, and reliability
Ensure data quality, integrity, and security across the data lifecycle
Collaborate with cross-functional teams to understand data requirements and deliver solutions
Monitor and troubleshoot data infrastructure and pipeline performance
Stay current with GCP updates and best practices to continuously improve data architecture
Proven experience in data engineering with GCP
Strong understanding of data modeling, warehousing, and pipeline architecture
Excellent problem-solving and communication skills
Should have Google Professional Data Engineer certification

Design and develop data pipelines using GCP services like BigQuery, Cloud Dataflow, Cloud Function, Composer, Cloud Pub/Sub, and Cloud Storage
Write efficient, scalable, and maintainable Python code for data processing, automation, and integration tasks
Implement ETL/ELT processes to ingest, transform, and store structured and unstructured data
Manage and optimize data storage solutions for performance, cost, and reliability
Ensure data quality, integrity, and security across the data lifecycle
Collaborate with cross-functional teams to understand data requirements and deliver solutions
Monitor and troubleshoot data infrastructure and pipeline performance
Stay current with GCP updates and best practices to continuously improve data architecture
Proven experience in data engineering with GCP
Strong understanding of data modeling, warehousing, and pipeline architecture
Excellent problem-solving and communication skills
Should have Google Professional Data Engineer certification