3-5 years of hands-on experience with Google Cloud Platform (GCP) data solutions.
Deep knowledge of BigQuery, including SQL optimization and slot management.
Practical experience with Dataflow (Apache Beam) in Python or Java.
Familiarity with orchestration tools like Cloud Composer (Apache Airflow).
Experience implementing Infrastructure as Code (IaC) using Terraform.
Responsibilities
Develop scalable Lambda/Kappa data pipelines for batch and real-time data.
Optimize and manage enterprise data warehouses in Google BigQuery.
Manage complex data workflows using orchestration tools like Cloud Composer.
Implement CI/CD pipelines for seamless data deployment.
Collaborate with analytics teams to create robust LookML models in Looker.
Optimize Looker queries and manage BigQuery costs effectively.
Establish data governance frameworks and ensure compliance with data privacy standards.
Benefits
Flexible work environment with remote options.
Opportunities for professional development and training.
Access to cutting-edge technology and tools.
Collaborative team culture focused on innovation.
Health and wellness programs to support employee well-being.
Full Job Description
Key Responsibilities Data Platform Architecture & Pipeline Engineering
Design & Build: Develop robust, scalable, and automated Lambda/Kappa data pipelines for both batch and real-time streaming data using GCP Dataflow (Apache Beam) and Cloud Data Fusion. Data Warehousing: Optimize and manage enterprise data warehouses in Google BigQuery, ensuring efficient storage, partitioning, clustering, and query performance. Orchestration: Work with orchestration tools like Cloud Composer (Apache Airflow) to manage complex data workflows and dependencies. CI/CD & DevOps: Implement Infrastructure as Code (IaC) using tools like Terraform and maintain CI/CD pipelines for seamless data deployment. Business Intelligence & Enablement
Semantic Modeling: Collaborate with analytics teams to model data and develop robust LookML models within Looker. Performance Tuning: Optimize Looker queries and BigQuery costs by implementing caching strategies, materialized views, and efficient BI Engine configurations. Data Governance & Quality (Preferred)
Compliance & Security: Implement data governance frameworks on GCP using Dataplex, Cloud Data Loss Prevention (DLP), and IAM policies to ensure data privacy and compliance. Data Lineage & Cataloging: Establish and maintain data catalogs, metadata management, and end-to-end data lineage. Data Quality: Build automated testing frameworks to monitor data quality, anomalies, and pipeline health. Qualifications & Skills Required Technical Skills : GCP Expertise: Minimum of 3-5 years of hands-on experience building production-grade data solutions on Google Cloud Platform. Core Tools: Deep, practical knowledge of BigQuery (SQL optimization, slot management) and Dataflow (Apache Beam in Python or Java).
About Virtusa Corporation
Virtusa Corporation is a global provider of digital business strategy, digital engineering, and information technology (IT) services and solutions. The company helps its clients transform their businesses through innovative technology solutions that enable them to improve customer engagement, increase operational efficiency, and drive revenue growth. Virtusa Corporation was founded in 1996 and is headquartered in Southborough, Massachusetts. The company has over 20,000 employees and operates in over 30 countries around the world. Virtusa Corporation is committed to sustainability and has received numerous awards for its environmental and social responsibility initiatives.
