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 solid advantage.

📌 Gcp Data Engineer (Hyderabad)
🏢 Randstad
📍 Hyderabad