Description

Required Skills**

- **Technical**: Proficiency in **SQL, Python, Java/Scala**, and distributed systems (Spark, Beam).
- **GCP Expertise**: Hands-on with **BigQuery, Dataflow, Dataproc, Pub/Sub, Composer (Airflow), and Terraform**.
- **DevOps**: Familiarity with **CI/CD, Git, and infrastructure-as-code**.

### **Nice to Have**

- **GCP Certifications** (e.g., Professional Data Engineer).
- Experience with **real-time processing, Vertex AI, or multi-cloud environments**.

### **Key Responsibilities**

- **Pipeline Development**: Build and optimize **ETL/ELT pipelines** using **Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Functions**.
- **Data Infrastructure**: Architect and manage **BigQuery, Cloud Storage, and Data Fusion** for efficient data ingestion, transformation, and storage.
- **Team Leadership**: Mentor junior engineers, review code, and establish **data engineering standards, CI/CD, and monitoring** (e.g., Cloud Monitoring, Logging).
- **Performance & Cost**: Optimize pipeline performance, query efficiency, and **GCP cost management** (e.g., slot reservations, partitioning).
- **Collaboration**: Work with data architects, scientists, and analysts to deliver **self-service data platforms** and support advanced analytics/ML use cases.
- **Data Quality & Governance**: Implement **data validation, lineage, and metadata management** (e.g., Data Catalog, dbt)

Key Skills

Education

Any Graduate