Data Architect and BigQuery/GCP

Roles & Responsibilities:

• Design and own BigQuery-based data warehouse/lakehouse architectures for large-scale analytics (preferably in Telco domains such as CDR, Billing, OSS/BSS).
• Define data modeling standards (dimensional modeling, wide tables, data products) with focus on performance and cost optimization (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, governance, and performance across platforms.
• Lead migration initiatives from 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 initiatives.

Critical Skills:

• 10–12 years of experience in Data Engineering/Architecture, with at least 3+ years in BigQuery/GCP.
• Strong expertise in BigQuery (schema design, performance tuning, cost optimization).
• Hands-on experience with GoogleSQL, Python, PySpark, and Airflow.
• Strong understanding of data warehousing concepts, ETL/ELT, and dimensional modeling.
• Experience with streaming technologies (Pub/Sub, Dataflow) and large-scale data processing.
• Exposure to on-prem and cloud data warehouses (Oracle, Teradata, Snowflake, Databricks, etc.).
• Experience with data migration, CI/CD pipelines, Git, and Terraform is an added advantage.