| Location | Dallas, TX (Remote) |
We are seeking a highly experienced, hands-on Principal Cloud Data Architect to lead the architecture, modernization, and implementation of enterprise-scale cloud data platforms leveraging Google Cloud Platform (GCP).
The ideal candidate will bring extensive experience in large-scale cloud migrations, modern data engineering, self-service analytics platforms, and enterprise data governance. This role requires a strong combination of architectural expertise, technical leadership, and strategic business understanding.
Key ResponsibilitiesEnterprise Data Architecture & Strategy
Define and execute scalable, secure, and future-ready cloud data architecture strategies aligned with enterprise objectives.
Design and implement modern, self-service data platforms that support distributed business and engineering teams.
Establish architectural standards, best practices, and long-term data modernization roadmaps.
Cloud Migration & Platform Modernization
Lead complex, enterprise-scale data migrations, particularly from AWS to GCP.
Architect and optimize petabyte-scale data ecosystems, ensuring performance, reliability, scalability, and cost efficiency.
Oversee cloud-native data integration, processing, storage, and analytics solutions.
Data Governance & Security
Establish comprehensive data governance, security, and compliance frameworks.
Implement IAM, VPC Service Controls, encryption, data masking, and automated governance using Dataplex.
Ensure enterprise-wide data quality, accessibility, and regulatory compliance.
Engineering Leadership & Automation
Provide architectural guidance to cross-functional data engineering, cloud infrastructure, and analytics teams.
Drive Infrastructure as Code (IaC) adoption using Terraform or Pulumi.
Promote DevOps, CI/CD, Agile methodologies, and automated cloud deployment practices.
Collaborate with senior leadership to communicate architectural decisions, business value, technical risks, and investment priorities.
Google Cloud Platform (GCP)
Data Storage & Warehousing: BigQuery, BigLake, BigQuery Omni, Google Cloud Storage.
Data Processing: Dataflow, Apache Beam, Dataproc, Apache Spark, Hadoop.
Workflow Orchestration: Cloud Composer, Apache Airflow.
Streaming & Messaging: Google Pub/Sub, Apache Kafka, Confluent.
Analytics & AI: Looker, Vertex AI, BigQuery ML.
Data Governance: Dataplex, IAM, VPC Service Controls, encryption and data protection.
Modern Data Engineering
Strong expertise in dbt, Airflow, and modern ELT/ETL frameworks.
Hands-on experience with Kubernetes, GKE, and containerized environments.
Proficiency in Terraform or Pulumi for infrastructure automation.
Strong understanding of distributed data processing, data lakehouse architectures, and enterprise data integration.
18 20 years of overall experience in Data Engineering, Data Warehousing, Business Intelligence, and enterprise data architecture.
Minimum 6+ years of hands-on experience with Google Cloud Platform (GCP).
Demonstrated success leading at least two enterprise-scale, petabyte-level cloud migration initiatives.
Proven experience designing and implementing enterprise-grade, self-service data platforms.
Strong background in AWS-to-GCP migration strategies and execution.
Experience leading large, cross-functional engineering teams in Agile and DevOps environments.
Excellent communication, stakeholder engagement, and technical decision-making skills.
Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or a related discipline.
Active Google Cloud Professional Data Engineer certification.
A verified Data Readiness Placement (DRP) ID with a score of 50 or above is highly desirable.
A seasoned cloud data architecture leader who combines deep technical expertise with hands-on implementation experience. The successful candidate will have a strong track record of architecting complex GCP data ecosystems, delivering large-scale cloud transformations, establishing governance frameworks, and guiding engineering teams through enterprise modernization initiatives.