GCP Data Architect: Modern Data Platform & Lineage

Virtusa Corporation; Columbus (OH); On-site; USD 120,000 - 180,000; Full time

Job summary

Virtusa Corporation in Columbus, OH is seeking a GCP Data Architect to design, modernize, and scale enterprise cloud data platforms on Google Cloud Platform.

You will lead end-to-end data transformation initiatives, implement data lineage and governance, and architect clocked time-series data processing with both real‑time and batch pipelines.

The role emphasizes secure, compliant data platforms with cost-optimized BigQuery schemas, Dataflow pipelines, and Dataproc/dbt for scalable analytics.

Responsibilities

• Data Transformation Architecture: Design, optimize, and standardize complex ETL/ELT data transformation frameworks using Google Cloud Dataflow (Apache Beam), Dataproc, and dbt to process large-scale structured and unstructured data.
• Data Lineage & Governance: Implement enterprise-wide data lineage tracking, metadata management, and impact analysis using GCP Dataplex and Data Catalog to ensure full traceability from ingestion to analytics.
• Date & Time-Series Data Management: Architect robust frameworks for date/time-based partitioning, temporal data modeling (SCD Type 2, bitemporal data), sliding time-window aggregations, and late‑arriving event processing in real‑time and batch pipelines.
• Modern GCP Data Platform Design: Lead the migration and architecture of scalable Data Lakes and Warehouses on Google BigQuery, ensuring optimal schema design, clustering, and cost optimization.
• Security & Compliance: Establish data governance, audit logging, IAM policies, and column/row‑level security to maintain compliance across all transformation and lineage layers.
• Data Transformation,
• Data Lineage & Cataloging,
• DevOps & Governance,
• GCP Core Platform

Job description

Virtusa Corporation in Columbus, OH is seeking a GCP Data Architect to design, modernize, and scale enterprise cloud data platforms on Google Cloud Platform.

You will lead end-to-end data transformation initiatives, implement data lineage and governance, and architect clocked time-series data processing with both real‑time and batch pipelines.

The role emphasizes secure, compliant data platforms with cost-optimized BigQuery schemas, Dataflow pipelines, and Dataproc/dbt for scalable analytics.