Principal Cloud Data Architect -Remote

Principal Cloud Data Architect GCP & Enterprise Data Platforms Job Overview

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 Responsibilities

Enterprise 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.

Required Technical Expertise

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.

Experience & Qualifications

• 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.

Mandatory Certification

• Active Google Cloud Professional Data Engineer certification.

Preferred Qualification

• A verified Data Readiness Placement (DRP) ID with a score of 50 or above is highly desirable.

Ideal Candidate Profile

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.