Google Cloud Platform Data Engineer

Responsibilities

Key Responsibilities:

1. Work effectively with fellow software engineers, product owners and other technical experts to deliver curated data products.
2. Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solution.
3. Design, develop, and deploy data pipelines using Dataflow, Dataproc, and other relevant GCP services.
4. Build and maintain data warehouses using BigQuery.
5. Implement data quality and validation processes.
6. Develop and maintain data schemas and models.
7. Collaborate with software engineers and other stakeholders to meet business requirements.
8. Manage and monitor GCP infrastructure using tools like Cloud Monitoring and Cloud Logging.
9. Implement security best practices for cloud-based applications.
10. Mentor and guide junior developers.

Qualifications

Qualifications:

1. Bachelor’s degree in computer science or a related field.
2. 8+ years of experience in software development, with at least 5 years on Google cloud technologies.
3. Expertise in Data ingestion and storage, Data Transformation and processing, Data analysis and visualization, Performance optimization and cost management, and a deep understanding, designing, data modeling, data integration, data warehousing and managing large-scale data storage system with below services: Big Query, Cloud Run, Cloud Function, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage and Data Studio, Dataflow, Dataproc, Cloud Build etc.,
4. Strong experience with infrastructure-as-code (IaC) tools like Terraform or Cloud Deployment Manager and Expertise in Tekton pipeline.
5. Deep understanding of GCP services, including Compute Engine, Kubernetes Engine (GKE), Cloud Storage, Cloud SQL, and Cloud Networking.
6. Extensive experience with DevOps practices and tools.
7. Expertise in Data encryption, Identity and Access Management and Cloud Security.