
Data Engineer
1 week ago
Job Summary:
Develop innovative data acquisition pipelines for large volumes of structured and unstructured data, including batch and real-time processing. This involves designing a robust infrastructure to handle the ingestion, processing, and storage of vast amounts of data.
Data Engineering Responsibilities
Create complex datasets based on business requirements and construct scalable 'big data' pipeline architecture.
- Identify opportunities for data acquisition via collaboration with stakeholders and business clients.
- Translate business needs to technical requirements.
- Leverage Google Cloud tools, such as Python, Data Flow, DataStream, CDC, Cloud Functions, Cloud Run, Pub Sub, BigQuery, and Cloud Storage, to integrate systems and data pipelines.
- Use logs & alerts to effectively monitor pipelines.
- Develop JSON messaging structure for integrating with various applications.
- Implement DevOps and CI/CD practices, using GitHub and 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.
Design and build an efficient ingestion pipeline using Rest API.
Recommend ways to improve data quality, reliability, and efficiency.
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