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. Skills: Data Architect, Gcp, Pyspark, data engineering , BigQuery, Python Experience: 10.00-14.00 Years