Gcp Data Engineer

Advanced Data Engineering & dbt Core:

• Pipeline Development & Orchestration: Design, implement, and maintain high-performance, automated ELT pipelines using dbt Core (self-hosted via Cloud Run) and BigQuery. Program and orchestrate serverless data flows using GCP Cloud Functions, Cloud Scheduler, and Dataflow (Python).
• Data Modeling & SQL Excellence: Develop complex, maintainable SQL solutions and perform advanced data modeling (partitioning, clustering) in BigQuery to reduce query latency and costs, serving as an efficient business-logic alternative to resource-intensive ML overhead.
• Infrastructure & API Integration: Provision GCP infrastructure using Infrastructure as Code (Terraform) and integrate external data sources (e.g., Salesforce, SAP BW, Workday, REST APIs) seamlessly into the existing data ecosystem.
• System Reliability & Operations: Proactively monitor system health and troubleshoot complex data flows, ensuring high availability and performance of our serverless architecture and automated process chains.
• Core Data Engineering: Deep proficiency in SQL and Python for complex data transformation, automation, and API integrations.
• GCP & Orchestration: Expert knowledge of the Google Cloud Platform (BigQuery, Cloud Functions, Cloud Run, Dataflow, Pub/Sub) and robust hands-on experience with self-hosted dbt Core.
• Architecture & DevOps: Strong experience provisioning infrastructure via Terraform and managing CI/CD pipelines using GitLab.
• Enterprise & MLOps (Nice-to-have): Practical knowledge of SAP BW, SAP Analytics, and Looker Studio. Familiarity with MLOps frameworks like Google Vertex AI and Kubeflow is a strong advantage.