GCP Big Query Architect

Key Responsibilities

• Design and implement scalable, secure, and high-performance data architectures on GCP, with BigQuery as the core data warehouse.
• Define end-to-end data architecture, including ingestion, transformation, storage, governance, and reporting.
• Lead migration of legacy data warehouses and ETL workloads to GCP and BigQuery.
• Design optimized BigQuery schemas, partitioning, clustering, and performance tuning strategies.
• Develop data pipelines using Cloud Dataflow, Dataproc, Cloud Composer, Cloud Functions, Pub/Sub, and Cloud Storage.
• Work with client business and technical teams to understand requirements and translate them into scalable cloud solutions.
• Establish best practices for data governance, security, metadata management, and data quality.
• Ensure compliance with enterprise security standards using IAM, encryption, audit logging, and networking best practices.
• Provide technical leadership, mentor development teams, and perform architecture and code reviews.
• Collaborate with DevOps teams to implement CI/CD pipelines and Infrastructure as Code (Terraform preferred).
• Support solution estimation, proposal preparation, technical presentations, and client workshops.
• Drive performance optimization, cost optimization, and operational excellence across GCP services.

Required Skills

• 10+ years of overall IT experience with at least 5+ years in GCP data engineering and architecture.
• Strong expertise in Google BigQuery architecture, optimization, and administration.
• Hands-on experience with Cloud Storage, Dataflow, Dataproc, Pub/Sub, Cloud Composer, BigQuery Transfer Service, Cloud Functions, and Cloud Run.
• Strong SQL, data modeling, dimensional modeling, and data warehousing expertise.
• Experience in migrating on-premise or legacy data platforms to GCP.
• Knowledge of ETL/ELT tools and modern data engineering practices.
• Experience with CI/CD, Terraform, Git, and DevOps practices.
• Good understanding of security, IAM, networking, and cloud governance.
• Experience integrating BI tools such as Looker, Tableau, or Power BI with BigQuery.
• Excellent communication, stakeholder management, and client-facing skills.

Preferred Qualifications

• Google Cloud Professional Data Engineer certification.
• Google Cloud Professional Cloud Architect certification.
• Experience with Dataplex, Data Catalog, and Vertex AI is an added advantage.
• Experience in Agile delivery methodologies and large enterprise transformation programs.