Develop, maintain, and deploy Python-based data processing applications to handle diverse data types.
Design and implement robust ETL and ELT pipelines to ensure efficient data ingestion, transformation, and loading from multiple sources such as APIs, files, databases, and third-party tools.
Utilize GCP-native tools including Pub/Sub, Cloud Functions, BigQuery, and Google Cloud Storage (GCS) to architect scalable, reliable, and performant data solutions.
Monitor, troubleshoot, and optimize data workflows and pipelines in production environments using tools like Cloud Monitoring and logging solutions.
Collaborate closely with cross-functional teams and stakeholders to understand data requirements and deliver high-quality data products.
Communicate effectively with customers and internal teams to resolve issues, gather feedback, and provide support.
