Description :

Roles & Responsibilities :

- Design and own BigQuery-based data warehouse/lakehouse architectures for large-scale analytics (preferably Telco domains like CDR, Billing, OSS/BSS).

- Define data modeling standards (dimensional, wide tables, data products) and optimize for performance and cost (partitioning, clustering).

- Architect and manage end-to-end data pipelines using BigQuery, Dataflow, Airflow (Cloud Composer), Pub/Sub, and Cloud Storage.

- Build and optimize batch and streaming ingestion frameworks for high-volume data.

- Ensure data quality, security, performance tuning, and governance across platforms.

- Lead migration of on-prem data warehouses to GCP/BigQuery.

- Collaborate with stakeholders, data engineers, and analysts to deliver scalable data solutions.

- Establish best practices, standards, and CI/CD frameworks for data engineering.

- Mentor team members and drive continuous improvement.

Job Description :

Critical Skills to Possess :

- 10-12 years in Data Engineering/Architecture with 3+ years in BigQuery/GCP.

- Strong expertise in BigQuery (schema design, optimization, cost control).

- Hands-on experience with GoogleSQL, Python, PySpark, Airflow.

- Solid understanding of data warehousing, ETL/ELT, dimensional modeling.

- Experience with streaming (Pub/Sub, Dataflow) and large-scale data processing.

- Exposure to on-prem & cloud DWs (Oracle, Teradata, Snowflake, Databricks, etc.

- Experience with data migration, CI/CD, Git, Terraform is a plus.