GCP Data Engineer

Role & responsibilities

Develop, construct, test and maintain data acquisition pipelines for large volumes of structed and unstructured data. This includes batch and real-time processing (in google cloud).

• Build large and complex datasets based on business requirements.
• Construct big data’ pipeline architecture.
• Identify opportunities for data acquisition via working with stakeholders and business clients.
• Translate business needs to technical requirements.
• Leverage a variety of tools in the Google Cloud Ecosystem such as Python, Data Flow, DataStream, CDC (Change Data Capture), Cloud Functions, Cloud Run, Pub Sub, BigQuery, Cloud Storage to integrate systems and data pipelines.
• Use logs & alerts to effectively monitor pipelines.
• Develop JSON messaging structure for integrating with various applications.
• Leverage DevOps and CI/CD practices (GitHub, Terraform) to ensure the reliability and scalability of data pipelines.
• Partition/Cluster and retrieve content in Big Query and use IAM roles & Policy Tags to secure the data.
• Use roles to secure access to datasets, authorized views to share data between projects.
• Design and build an ingestion pipeline using Rest API.
• Recommends ways to improve data quality, reliability, and efficiency.