BigQuery Architect

10-12 Years

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Early Applicant

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.

Preferred Qualifications

Roles & Responsibilities

Roles And 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.